{"id":28805,"date":"2024-04-14T11:23:03","date_gmt":"2024-04-14T11:23:03","guid":{"rendered":"https:\/\/electropeak.com\/learn\/?p=28805"},"modified":"2024-04-14T11:30:39","modified_gmt":"2024-04-14T11:30:39","slug":"raspberry-pi-pico-voice-recognition-and-wake-word-using-ai","status":"publish","type":"post","link":"https:\/\/electropeak.com\/learn\/raspberry-pi-pico-voice-recognition-and-wake-word-using-ai\/","title":{"rendered":"Raspberry Pi Pico Voice Recognition And Wake Word Using AI"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"28805\" class=\"elementor elementor-28805\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2ad44e1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2ad44e1\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e7fadd6\" data-id=\"e7fadd6\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b1eb66d elementor-widget elementor-widget-heading\" data-id=\"b1eb66d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Introduction<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8aca845 elementor-widget elementor-widget-text-editor\" data-id=\"8aca845\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Welcome to the world of innovation with Raspberry Pi Pico! This article explores voice recognition and wake word detection using machine learning techniques. Discover how to leverage Raspberry Pi Pico&#8217;s capabilities to create intelligent devices that respond to voice commands. Join us as we explore the exciting possibilities for smart home technology, robotics, and more.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-409c74e elementor-widget elementor-widget-image\" data-id=\"409c74e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-intro.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-intro\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODA4IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1pbnRyby5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-intro-1200x750.jpg\" class=\"attachment-large size-large wp-image-28808\" alt=\"Voice recog RPI pico\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-intro-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-intro-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ef29319 elementor-widget elementor-widget-text-editor\" data-id=\"ef29319\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Imagine you could use the machine learning capability on microcontrollers such as Raspberry Pi Pico. By integrating the power of machine learning and Raspberry Pi Pico using Edge Impulse, you can open up a whole new world of possibilities.\u00a0<\/p><p>Raspberry Pi Pico is a low-cost yet powerful platform, and Edge Impulse provides a visual development environment for training and deploying machine learning models. Together, they can bring your ideas to life, in ways you never imagined.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4187c1b elementor-widget elementor-widget-heading\" data-id=\"4187c1b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What You Will Learn<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0e1b365 elementor-widget elementor-widget-text-editor\" data-id=\"0e1b365\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>The concept of machine learning<\/li><li>How to create models from files<\/li><li>How to implement machine learning on Raspberry Pi Pico<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5dfee30 elementor-widget elementor-widget-heading\" data-id=\"5dfee30\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How to Implement Machine Learning on Raspberry Pi Pico<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-92eac25 elementor-widget elementor-widget-text-editor\" data-id=\"92eac25\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Before we get into building the machine learning models, let\u2019s start with the basics of machine learning. Machine learning is a subset of AI, focusing on algorithms and models that can learn from data and make predictions or decisions without explicit programming.\u00a0<\/p><p>There are 3 types of machine learning: supervised, unsupervised, and reinforcement learning. Here is how they work:<\/p><p><b>Supervised Learning: <\/b>The model learns from labeled data, where each data point is associated with a label or target output.\u00a0<\/p><p><b>Unsupervised Learning:<\/b> It deals with unlabeled data, aiming to find patterns or structures in the data.\u00a0<\/p><p><b>Reinforcement Learning: <\/b>It relies on a reward-based system where the model learns by trial and error to maximize rewards.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7de5376 elementor-widget elementor-widget-image\" data-id=\"7de5376\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-TypeOfLearning.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-TypeOfLearning\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODA5IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1UeXBlT2ZMZWFybmluZy5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-TypeOfLearning-1200x750.jpg\" class=\"attachment-large size-large wp-image-28809\" alt=\"Type Of Learning\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-TypeOfLearning-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-TypeOfLearning-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f4ee7ae elementor-widget elementor-widget-heading\" data-id=\"f4ee7ae\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Machine Learning Algorithms for Raspberry Pi Pico and Arduino<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6d51a51 elementor-widget elementor-widget-text-editor\" data-id=\"6d51a51\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>To implement machine learning algorithms on Raspberry Pi Pico and Arduino, we need to keep in mind their limitations. These microcontrollers have limited memory and computational power, which means we should select algorithms that are lightweight and optimized for environments with limited resources.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-05711b2 elementor-widget elementor-widget-heading\" data-id=\"05711b2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Collecting and preparing Data for Machine learning<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-41996a4 elementor-widget elementor-widget-text-editor\" data-id=\"41996a4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>To build machine learning models effectively, you need to collect and prepare your data. Data collection includes collecting relevant datasets that contain the features or variables that you want your model to learn from. You can obtain these datasets from various sources such as online data, sensor data, or manual data collection.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9f6e0d9 elementor-widget elementor-widget-heading\" data-id=\"9f6e0d9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">How Edge Impulse Contributes to Machine Learning Integration<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-45751ed elementor-widget elementor-widget-text-editor\" data-id=\"45751ed\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Edge Impulse is an advanced development platform that simplifies the process of integrating machine learning with embedded systems such as Raspberry Pi Pico. The platform provides a user-friendly interface to collect, preprocess, train, and deploy machine learning models directly on your device.<\/p><p>To get started with Edge Impulse, you won\u2019t need in-depth knowledge of machine learning algorithms or coding expertise. The platform offers a wide range of tools and features that enable developers of all skill levels to utilize the power of machine learning. From data collection to model deployment, Edge Impulse simplifies the entire process and is accessible to anyone interested in building intelligent applications.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fa4c227 elementor-widget elementor-widget-image\" data-id=\"fa4c227\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EdgeImpulseIntro-1200x750.jpg\" class=\"attachment-large size-large wp-image-28813\" alt=\"Edge Impulse\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EdgeImpulseIntro-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EdgeImpulseIntro-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9628721 elementor-widget elementor-widget-text-editor\" data-id=\"9628721\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>One of the key benefits of Edge Impulse is pre-processing and integrated data management. This platform supports a wide range of sensors and data types, allowing you to capture and process data from a variety of resources. Whether you&#8217;re dealing with accelerometer data, audio signals, or image inputs, Edge Impulse provides the tools you need to preprocess the data before training machine learning models. This eliminates the need for manual data processing and saves you time and effort during the development process. In addition, Edge Impulse has a visual interface for labeling and annotating data, simplifying the process of building high-quality datasets for training your models.\u00a0<\/p><p>As mentioned, integrating machine learning with Raspberry Pi Pico using Edge Impulse has a lot of benefits: imagine you could build your desired smart home or a robot that could move around on its own. This way, you can develop applications that were once possible only by advanced hardware and complicated algorithms.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7ca957c elementor-widget elementor-widget-heading\" data-id=\"7ca957c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Machine Learning with Raspberry Pi Pico: Benefits<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1b2ba57 elementor-widget elementor-widget-text-editor\" data-id=\"1b2ba57\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Machine learning with Raspberry Pi Pico has countless benefits for developers and enthusiasts. Let\u2019s review some key factors:<\/p><p><b>1. Low-cost platform: <\/b>Raspberry Pi Pico offers a cost-effective solution for building embedded systems. Costing only a few dollars, it\u2019s an affordable option for enthusiasts, students, and professionals.\u00a0<\/p><p><b>2. Versatile Development Environment:<\/b> Raspberry Pi Pico\u2014a Versatile development environment \u2014is compatible with various programming languages, including MicroPython and C\/C++. This flexibility allows developers to choose the language they are most comfortable with. Whether you are into Python or C\/C++, Raspberry Pi Pico provides a familiar environment for developing practical AI applications.\u00a0<\/p><p><b>3. Real-time processing: <\/b>With this method, you can train and deploy machine learning models directly on the device itself, without the need for a cloud connection. This capability makes it possible to run programs that require an immediate response, such as robotics projects or real-time monitoring systems.<\/p><p><b>4. Privacy and Security:<\/b> By processing data locally on the device, you can ensure that sensitive and private information remains secure. This is especially important when working with personal or confidential data.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f35075 elementor-widget elementor-widget-heading\" data-id=\"4f35075\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Required Materials<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c27bfcf elementor-widget elementor-widget-image\" data-id=\"c27bfcf\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-required-materials-1200x750.jpg\" class=\"attachment-large size-large wp-image-28817\" alt=\"required materials\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-required-materials-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-required-materials-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73d929a elementor-widget elementor-widget-html\" data-id=\"73d929a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"hardware-list\">\r\n\t<a href=\"https:\/\/electropeak.com\/raspberry-pi-pico\" target=\"_blank\">\r\n\t    <div class=\"name\">Raspberry Pi Pico<\/div>\r\n\t    <i class=\"fas fa-times pl-2\"><\/i>\r\n\t    <div class=\"qty\">1<\/div>\r\n\t    <i class=\"fa fa-external-link-alt\"><\/i>\r\n\t<\/a>\r\n\t<a href=\"\" target=\"_blank\">\r\n\t    <div class=\"name\">Micro USB Cable<\/div>\r\n\t    <i class=\"fas fa-times pl-2\"><\/i>\r\n\t    <div class=\"qty\">1<\/div>\r\n\t    <i class=\"fa fa-external-link-alt\"><\/i>\r\n\t<\/a>\r\n\t<a href=\"https:\/\/electropeak.com\/cjmcu-max9814-high-performance-microphone-agc-amplifier-module https:\/\/thecaferobot.com\/store\/cjmcu-max9814-high-performance-microphone-agc-amplifier-module\" target=\"_blank\">\r\n\t    <div class=\"name\">MAX9814 Microphone Amplifier Module<\/div>\r\n\t    <i class=\"fas fa-times pl-2\"><\/i>\r\n\t    <div class=\"qty\">1<\/div>\r\n\t    <i class=\"fa fa-external-link-alt\"><\/i>\r\n\t<\/a>\r\n\t<a href=\"https:\/\/electropeak.com\/21cm-40p-male-to-female-jumper-wire\" target=\"_blank\">\r\n\t    <div class=\"name\">Male-to-Female Jumper Wire<\/div>\r\n\t    <i class=\"fas fa-times pl-2\"><\/i>\r\n\t    <div class=\"qty\">1<\/div>\r\n\t    <i class=\"fa fa-external-link-alt\"><\/i>\r\n\t<\/a>\r\n\t<a href=\"https:\/\/electropeak.com\/micro-switch-push-button https:\/\/thecaferobot.com\/store\/6x6x8-push-button\" target=\"_blank\">\r\n\t    <div class=\"name\">Push Button (Micro Switch)<\/div>\r\n\t    <i class=\"fas fa-times pl-2\"><\/i>\r\n\t    <div class=\"qty\">1<\/div>\r\n\t    <i class=\"fa fa-external-link-alt\"><\/i>\r\n\t<\/a>\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-925403a elementor-widget elementor-widget-heading\" data-id=\"925403a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Voice Recognition with Raspberry Pi Pico<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dd6c40d elementor-widget elementor-widget-text-editor\" data-id=\"dd6c40d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Keyword spotting (KWS) is a technology used in a wide variety of applications. With this technology, you can interact with your device without using your hands. Recognizing the famous wake-up words, such as OK Google, Alexa, Hey Siri, or Cortana is a specific application of this technology, where the smart assistant continuously listens to the magical phrase before starting to interact with the device.\u00a0\u00a0<\/p><p>Now, let\u2019s see how we can use KWS on Raspberry Pi Pico using Edge Impulse:<\/p><p>First, we will design a model based on Mel-frequency cepstral coefficients (MFCC), which is one of the most popular voice recognition features. Then, we will explain how to extract MFCCs from voice samples and train a machine learning (ML) model.<\/p><p>Our goal is to learn about the development of a KWS application using Edge Impulse and familiarize ourselves with acquiring voice data from an analog-to-digital converter (ADC).<\/p><p>To do that, we will implement the following instructions:<\/p><ul><li>Collect relevant audio data<\/li><li>Extract MFCC features from voice samples<\/li><li>Design and train an Artificial Neural Network (ANN) model<\/li><li>Build a circuit with Raspberry Pi Pico<\/li><li>Take voice samples using ADC and timer interrupts<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-acec601 elementor-widget elementor-widget-heading\" data-id=\"acec601\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Building a Model in the Edge Impulse Environment<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cf32564 elementor-widget elementor-widget-text-editor\" data-id=\"cf32564\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Create an account on the Edge Impulse website by visiting this <a href=\"https:\/\/studio.edgeimpulse.com\/\">link<\/a>.\u00a0<\/li><li>Go to the &#8220;Projects&#8221; section, click on the &#8220;+Create new project&#8221; button, choose a name, and click &#8220;Create new project&#8221; as shown in the image below.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2202985 elementor-widget elementor-widget-image\" data-id=\"2202985\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-1.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 1\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODIxIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xLmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-1-1200x750.jpg\" class=\"attachment-large size-large wp-image-28821\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-1-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-1-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1c40b72 elementor-widget elementor-widget-text-editor\" data-id=\"1c40b72\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Go to the Dashboard panel and adjust the settings in the &#8220;Project info&#8221; section.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ec2c4cb elementor-widget elementor-widget-image\" data-id=\"ec2c4cb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-2.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 2\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODIyIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0yLmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-2-1200x750.jpg\" class=\"attachment-large size-large wp-image-28822\" alt=\"\u2022 Go to the Dashboard panel and adjust the settings in the &quot;Project info&quot; section\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-2-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-2-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bff6b25 elementor-widget elementor-widget-text-editor\" data-id=\"bff6b25\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Download this <a href=\"https:\/\/cdn.edgeimpulse.com\/datasets\/keywords2.zip\">compressed file<\/a> and then extract it.<\/li><\/ul><div>In the Dashboard panel, click on the &#8220;Add existing data&#8221; button to open a new window. In that window, select the &#8220;Upload data&#8221; option. Set the &#8220;Upload info category&#8221; to &#8220;Training&#8221; and enter the desired label. Then, upload the relevant files by clicking on &#8220;Choose files.&#8221;<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8384e0c elementor-widget elementor-widget-image\" data-id=\"8384e0c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-3.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 3\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODIzIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0zLmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-3-1200x750.jpg\" class=\"attachment-large size-large wp-image-28823\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-3-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-3-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-58c403d elementor-widget elementor-widget-text-editor\" data-id=\"58c403d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>We have assigned the labels &#8220;01_Yes&#8221;, &#8220;02_No&#8221;, and &#8220;03_Unknown&#8221; for the files in the &#8220;yes&#8221;, &#8220;no&#8221;, and &#8220;unknown&#8221; folders, respectively.<\/p><p>Once you click the Upload button, the files will be uploaded.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cf0c450 elementor-widget elementor-widget-image\" data-id=\"cf0c450\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-4.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 4\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODI0IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS00LmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-4-1200x750.jpg\" class=\"attachment-large size-large wp-image-28824\" alt=\"Upload the file\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-4-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-4-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c2fe95a elementor-widget elementor-widget-text-editor\" data-id=\"c2fe95a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Once uploaded, the total duration of the loaded voice files will be displayed at the top of the &#8220;Data acquisition&#8221; page.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5f2bea8 elementor-widget elementor-widget-image\" data-id=\"5f2bea8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-5.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 5\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODI1IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS01LmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-5-1200x750.jpg\" class=\"attachment-large size-large wp-image-28825\" alt=\"the total duration of the loaded voice files will be displayed at the top of the &quot;Data acquisition&quot; page\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-5-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-5-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-12f92ea elementor-widget elementor-widget-text-editor\" data-id=\"12f92ea\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>In the \u201cImpulse design\u201d panel, start by determining the required features for training the neural network. To do this, we utilize Mel-frequency cepstral coefficients (MFCC) as features.<\/li><\/ul><p>As shown in the image below, begin designing your first \u201cImpulse\u201d by clicking on the &#8220;Create impulse&#8221; option in the left menu:<\/p><div>\u00a0<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5b5ef41 elementor-widget elementor-widget-image\" data-id=\"5b5ef41\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-6-1200x750.jpg\" class=\"attachment-large size-large wp-image-28826\" alt=\"create impulse\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-6-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-6-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f97f948 elementor-widget elementor-widget-text-editor\" data-id=\"f97f948\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In the \u201cCreate impulse\u201d section, ensure that the &#8220;Window size&#8221; field in the &#8220;Time series data&#8221; section is set to 1000 ms, and the &#8220;window increase&#8221; field to 500 ms.<\/p><p>The &#8220;Window increase&#8221; parameter is specifically designed for &#8220;Continuous KWS&#8221;, where there is a continuous voice stream, and the exact start time of speech is unknown. In this scenario, we need to divide the voice stream into windows or sections of equal length and perform machine learning inference on each of them. As shown in the figure below, &#8220;Window size&#8221; represents the length of each window, while &#8220;Window increase&#8221; indicates the time interval between two consecutive sections.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96042c5 elementor-widget elementor-widget-image\" data-id=\"96042c5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Window-Size-1200x750.jpg\" class=\"attachment-large size-large wp-image-28827\" alt=\"Window Size\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Window-Size-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Window-Size-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0e2324b elementor-widget elementor-widget-text-editor\" data-id=\"0e2324b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The &#8220;Window size&#8221; depends on the length of the training sample (1 second) and may affect the accuracy of the results. On the other hand, the &#8220;Window increase&#8221; does not affect the learning results but rather the likelihood of correctly detecting the start of speech. In fact, the lower the \u201cWindow increase\u201d, the higher the chance of correctly detecting the start point of the speech. However, the proper value for \u201cWindow increase\u201d depends on the model\u2019s delay.\u00a0\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a3ae837 elementor-widget elementor-widget-image\" data-id=\"a3ae837\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-7.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 7\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODMxIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS03LmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-7-1200x750.jpg\" class=\"attachment-large size-large wp-image-28831\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-7-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-7-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d6bf5b4 elementor-widget elementor-widget-text-editor\" data-id=\"d6bf5b4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p class=\"MsoNormal\" style=\"direction: ltr\">Now, let\u2019s design a processing block for extracting MFCC features from recorded voice samples:<\/p><p>\u00a0<\/p><p class=\"MsoNormal\" style=\"direction: ltr\">1. Click on \u201cAdd a processing block\u201d and add Audio (MFCC).<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d876b40 elementor-widget elementor-widget-image\" data-id=\"d876b40\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-8.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 8\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODMyIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS04LmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-8-1200x750.jpg\" class=\"attachment-large size-large wp-image-28832\" alt=\"Click on \u201cAdd a processing block\u201d and add Audio (MFCC).\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-8-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-8-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3b99504 elementor-widget elementor-widget-text-editor\" data-id=\"3b99504\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>2. Click on \u201cAdd a learning block\u201d and add Classification (Keras).<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-64fcaca elementor-widget elementor-widget-image\" data-id=\"64fcaca\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-9.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 9\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODMzIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS05LmpwZyJ9\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-9-1200x750.jpg\" class=\"attachment-large size-large wp-image-28833\" alt=\"Click on \u201cAdd a learning block\u201d and add Classification (Keras).\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-9-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-9-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3048f3f elementor-widget elementor-widget-text-editor\" data-id=\"3048f3f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>According to the image below, the \u201cOutput features\u201d block should report three output classes for identification (01_Yes, 02_No, 03_Unknown).<\/p><p>3. Click on \u201cSave Impulse.\u201d<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e90cc04 elementor-widget elementor-widget-image\" data-id=\"e90cc04\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-10-1200x750.jpg\" class=\"attachment-large size-large wp-image-28834\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-10-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-10-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-69ed896 elementor-widget elementor-widget-text-editor\" data-id=\"69ed896\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>4. Click on \u201cMFCC\u201d in the \u201cImpulse design\u201d category.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d1312c0 elementor-widget elementor-widget-image\" data-id=\"d1312c0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-11-1200x750.jpg\" class=\"attachment-large size-large wp-image-28835\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-11-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-11-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3e6a65e elementor-widget elementor-widget-text-editor\" data-id=\"3e6a65e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>5. Adjust the parameters that affect the MFCC feature extraction.<\/p><p>Here, you can adjust the parameters that affect the extraction of MFCC features such as the number of cepstral coefficients and the number of triangular filters applied for Mel scaling. In this tutorial, all MFCC parameters are kept at their default values.\u00a0<\/p><p>There is also a parameter for the \u201cpre-emphasis\u201d stage at the bottom of the page. The \u201cpre-emphasis\u201d stage is performed before generating a spectrogram; we increase the energy at the highest frequencies in order to reduce the noise. If the \u201cCoefficient value\u201d is zero, there won\u2019t be any emphasis on the input signal. Here, the \u201cpre-emphasis\u201d parameter is kept at its default value.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-42c0933 elementor-widget elementor-widget-image\" data-id=\"42c0933\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-12.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 12\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODM2IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xMi5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-12-1200x750.jpg\" class=\"attachment-large size-large wp-image-28836\" alt=\"the \u201cpre-emphasis\u201d parameter is kept at its default value\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-12-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-12-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7e8c4e6 elementor-widget elementor-widget-text-editor\" data-id=\"7e8c4e6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>6. Click on \u201cGenerate features\u201d to extract MFCC features from the training samples.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9af307d elementor-widget elementor-widget-image\" data-id=\"9af307d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-13.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 13\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODM3IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xMy5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-13-1200x750.jpg\" class=\"attachment-large size-large wp-image-28837\" alt=\"Click on \u201cGenerate features\u201d to extract MFCC features from the training samples\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-13-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-13-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eea7ec2 elementor-widget elementor-widget-text-editor\" data-id=\"eea7ec2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>At the end, Edge Impulse returns the \u201cJob completed\u201d message in the console output.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c368327 elementor-widget elementor-widget-image\" data-id=\"c368327\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-14.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 14\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODM4IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xNC5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-14-1200x750.jpg\" class=\"attachment-large size-large wp-image-28838\" alt=\"Edge Impulse returns the \u201cJob completed\u201d message in the console output.\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-14-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-14-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-efe9320 elementor-widget elementor-widget-text-editor\" data-id=\"efe9320\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Now, you have successfully extracted MFCC features from all recorded voice samples.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dff8e6a elementor-widget elementor-widget-heading\" data-id=\"dff8e6a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Feature Extraction Results<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8e473b7 elementor-widget elementor-widget-text-editor\" data-id=\"8e473b7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>After extracting MFCC features, we can use the \u201cFeature explorer\u201d tool and a 3D scatter plot to examine the generated training dataset, similar to the image below.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3d4eee7 elementor-widget elementor-widget-image\" data-id=\"3d4eee7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-15.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 15\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODQyIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xNS5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-15-1200x750.jpg\" class=\"attachment-large size-large wp-image-28842\" alt=\"use the \u201cFeature explorer\u201d tool and a 3D scatter plot to examine the generated training dataset\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-15-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-15-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b7713ee elementor-widget elementor-widget-text-editor\" data-id=\"b7713ee\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>We should infer from the plot above whether the input features are suitable for our issue. If so, the output classes (except for the unknown output class) should be well separated.\u00a0<\/p><p>You can view the temporary memory usage and data processing time in the \u201cOn-device performance\u201d section related to MFCC.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-57e0f17 elementor-widget elementor-widget-image\" data-id=\"57e0f17\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-16-1200x750.jpg\" class=\"attachment-large size-large wp-image-28843\" alt=\"On-device performance\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-16-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-16-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-25d707b elementor-widget elementor-widget-text-editor\" data-id=\"25d707b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The processing time (delay) and maximum RAM usage (data memory) are estimated in the \u201cProject info\u201d section according to the device selected in the \u201cDashboard.\u201d\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-76418b8 elementor-alert-info elementor-widget elementor-widget-alert\" data-id=\"76418b8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"alert.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-alert\" role=\"alert\">\n\n\t\t\t\t\t\t<span class=\"elementor-alert-title\">Tip<\/span>\n\t\t\t\n\t\t\t\t\t\t<span class=\"elementor-alert-description\">If you have carefully read and understood the definition and adjustment of \u201cWindow size\u201d and \u201cWindow increase,\u201d you must have realized that continuous voice recognition can only be performed if the processing time is much shorter than the voice sampling time. In the above image, the processing time is 959ms, which means that after speech sampling, the processor performance is fully engaged for 1 second, and sampling is not possible. \nTherefore, Raspberry Pi Pico can\u2019t recognize the voice continuously.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a532dcc elementor-widget elementor-widget-heading\" data-id=\"a532dcc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">NN Model: Design and Train<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5c0a1fd elementor-widget elementor-widget-text-editor\" data-id=\"5c0a1fd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In this tutorial, we will use the following NN architecture for speech recognition:\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3a43464 elementor-widget elementor-widget-image\" data-id=\"3a43464\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-17.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 17\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODQ0IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xNy5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-17-1200x750.jpg\" class=\"attachment-large size-large wp-image-28844\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-17-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-17-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d583fa1 elementor-widget elementor-widget-text-editor\" data-id=\"d583fa1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>This model consists of two 2D convolution layers, one dropout layer, and a fully connected layer followed by a \u201csoftmax\u201d activation.<\/p><p>MFCC features are the network input which are extracted from one-second voice samples.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a7e1cf4 elementor-widget elementor-widget-heading\" data-id=\"a7e1cf4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Preparation<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d42c236 elementor-widget elementor-widget-text-editor\" data-id=\"d42c236\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h4>To do this, we only need to know how to design and train an NN model in Edge Impulse.\u00a0<\/h4><p>Depending on the selected learning block, Edge Impulse employs various ML frameworks for training. Here, Edge Impulse uses TensorFlow and Keras for the \u201cclassification\u201d learning block.\u00a0<\/p><p><b>You can design the model in two ways:\u00a0<\/b><\/p><ul><li><strong>Visual (simple way):<\/strong> It\u2019s the quickest way and is done by the user interface. Edge Impulse provides some basic NN blocks and their architecture settings, which can be very helpful if you are new to deep learning (DL).\u00a0<\/li><li><strong>Keras Code (advanced way):<\/strong> If you want to have more control over the network architecture, you can directly edit the Keras code in the web browser.\u00a0<\/li><\/ul><h4>Steps to Follow<\/h4><p>Click on the neural network (Keras) in \u201cImpulse design\u201d and follow the steps below to design and train the NN model as shown in the network structure diagram.<br \/>1. Select the &#8220;2D Convolution&#8221; architecture preset and delete the Dropout layer in the middle of the two convolution layers.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2e9f472 elementor-widget elementor-widget-image\" data-id=\"2e9f472\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-18.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 18\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODQ1IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xOC5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-18-1200x750.jpg\" class=\"attachment-large size-large wp-image-28845\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-18-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-18-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a5967df elementor-widget elementor-widget-text-editor\" data-id=\"a5967df\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>2. Click on the \u22ee\u00a0 icon to enter Keras mode (professional). In the code section, remove the MaxPooling2D layers.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-27f283a elementor-widget elementor-widget-image\" data-id=\"27f283a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-19.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 19\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODQ2IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0xOS5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-19-1200x750.jpg\" class=\"attachment-large size-large wp-image-28846\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-19-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-19-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-612bd75 elementor-widget elementor-widget-text-editor\" data-id=\"612bd75\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Set the first convolution layer&#8217;s strides to (2,2) as shown in the code below.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-91db4cc elementor-widget elementor-widget-html\" data-id=\"91db4cc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<pre class=\"line-numbers lang-arduino\"><code>\r\nmodel.add(Conv2D(8, strides=(2,2), kernel_size=3, activation='relu', kernel_constraint=tf.keras. constraints.MaxNorm(1), padding='same'))\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c0113bd elementor-widget elementor-widget-text-editor\" data-id=\"c0113bd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The pooling layer is a subsampling technique that helps decrease the amount of data sent through the network, which in turn reduces the chances of overfitting. However, it can lead to delays and higher RAM usage. In devices like microcontrollers with limited memory, RAM is a valuable resource, and we need to use it carefully. Therefore, we take non-unit steps in the convolution layers to reduce the size of spatial dimensions. This approach usually has better performance as we completely skip the computations of pooling layers and have fewer output elements to process, resulting in faster convolution layers.<\/p><p>3. Click on \u201cStart training.\u201d<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c4f2916 elementor-widget elementor-widget-image\" data-id=\"c4f2916\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-20.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 20\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODQ3IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0yMC5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-20-1200x750.jpg\" class=\"attachment-large size-large wp-image-28847\" alt=\"click start training\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-20-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-20-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-be93cd0 elementor-widget elementor-widget-text-editor\" data-id=\"be93cd0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>During the training process, the output console reports the accuracy and error of the training dataset and their validation after every stage.\u00a0\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f5c78a elementor-widget elementor-widget-image\" data-id=\"4f5c78a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-21.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 21\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODQ4IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0yMS5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-21-1200x750.jpg\" class=\"attachment-large size-large wp-image-28848\" alt=\"the output console reports the accuracy and error of the training dataset and their validation after every stage\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-21-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-21-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-61c4ea4 elementor-widget elementor-widget-text-editor\" data-id=\"61c4ea4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>At the end of training, we can evaluate the model\u2019s performance (accuracy and error), the confusion matrix, and the estimated performance of the device on the same page.\u00a0\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1f7477e elementor-alert-info elementor-widget elementor-widget-alert\" data-id=\"1f7477e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"alert.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-alert\" role=\"alert\">\n\n\t\t\t\t\t\t<span class=\"elementor-alert-title\">Tip<\/span>\n\t\t\t\n\t\t\t\t\t\t<span class=\"elementor-alert-description\">If the accuracy is 100%, it means that the model may be overfitting the data. To prevent this, you can add more data to your training set or decrease the learning level.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3644903 elementor-widget elementor-widget-text-editor\" data-id=\"3644903\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>If you are not satisfied with the accuracy, we recommend collecting more data and retraining the model.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fdd6738 elementor-alert-success elementor-widget elementor-widget-alert\" data-id=\"fdd6738\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"alert.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-alert\" role=\"alert\">\n\n\t\t\t\t\t\t<span class=\"elementor-alert-title\">Success!<\/span>\n\t\t\t\n\t\t\t\t\t\t<span class=\"elementor-alert-description\">You have built an NN model for speech recognition of Yes and No!<\/span>\n\t\t\t\n\t\t\t\t\t\t<button type=\"button\" class=\"elementor-alert-dismiss\" aria-label=\"Dismiss this alert.\">\n\t\t\t\t\t\t\t\t\t<span aria-hidden=\"true\">&times;<\/span>\n\t\t\t\t\t\t\t<\/button>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c1a38a1 elementor-widget elementor-widget-text-editor\" data-id=\"c1a38a1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Now, you can download the created model as an Arduino library. To do that, click on Deployment -&gt; Arduino library -&gt; Build.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-452749c elementor-widget elementor-widget-image\" data-id=\"452749c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-22.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-EI 22\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODQ5IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1FSS0yMi5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-22-1200x750.jpg\" class=\"attachment-large size-large wp-image-28849\" alt=\"click on Deployment -&gt; Arduino library -&gt; Build\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-22-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-EI-22-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4de544c elementor-widget elementor-widget-heading\" data-id=\"4de544c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">A Circuit w\/ Raspberry Pi Pico: Voice-Controlled LED<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d704945 elementor-widget elementor-widget-text-editor\" data-id=\"d704945\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Raspberry Pi Pico only has a microcontroller on it. Therefore, you need to build a simple circuit to control voice on this platform.\u00a0<\/p><p>To start, we will need a few components: a Raspberry Pi Pico, an electret microphone with a MAX9814 amplifier, and a push button.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ac02d51 elementor-widget elementor-widget-heading\" data-id=\"ac02d51\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">MAX9814 Microphone Amplifier in a Nutshell<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0c07134 elementor-widget elementor-widget-text-editor\" data-id=\"0c07134\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The microphone used in this tutorial is the low-cost MAX9814 electret microphone amplifier.\u00a0<\/p><p>The signal coming from the microphone is usually small and needs amplification for recording and analysis. For this reason, the microphone output is amplified with the MAX9814 chip, which is an automatic gain control (AGC) amplifier. AGC allows recording speech in environments where the background noise level varies unpredictably. Therefore, MAX9814 automatically adjusts the gain to always distinguish the desired sound.<\/p><p>The amplifier requires a power supply between 2.7 and 5.5V and generates an output with a maximum peak-to-peak voltage of 2V at a DC bias of 1.25V. Therefore, you can easily connect the device to microcontrollers that operate at a voltage level of 3.3V.<\/p><p>The microphone module has five pins as shown in the image below.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-895e032 elementor-widget elementor-widget-image\" data-id=\"895e032\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-MAX9814-pinout.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-MAX9814-pinout\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODUwIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1NQVg5ODE0LXBpbm91dC5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-MAX9814-pinout-1200x750.jpg\" class=\"attachment-large size-large wp-image-28850\" alt=\"Voice recog RPI pico MAX9814 pinout\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-MAX9814-pinout-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-MAX9814-pinout-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6b5466c elementor-widget elementor-widget-heading\" data-id=\"6b5466c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Wiring<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-80ac40d elementor-widget elementor-widget-text-editor\" data-id=\"80ac40d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Wire up the components as shown below.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-538702e elementor-widget elementor-widget-image\" data-id=\"538702e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-wiring.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-wiring\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODU0IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby13aXJpbmcuanBnIn0%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-wiring-1200x750.jpg\" class=\"attachment-large size-large wp-image-28854\" alt=\"Voice recog RPI pico wiring\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-wiring-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-wiring-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d85f2f3 elementor-widget elementor-widget-heading\" data-id=\"d85f2f3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Voice Sampling on Raspberry Pi Pico w\/ ADC and Timer Interrupts<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5e7127a elementor-widget elementor-widget-text-editor\" data-id=\"5e7127a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Now, all the components are connected to Raspberry Pi Pico, and the only thing left is the code.\u00a0\u00a0<\/p><p>When we press the push button, the code records the voice for 1 second, extracts its features, and enters the data into an artificial neural network for classification. Finally, the result will be displayed as text on the serial monitor.\u00a0<\/p><p>So, the first step is to read the voice signal. For this, you need to use an analog-to-digital converter (ADC). The RP2040 chip on Raspberry Pi Pico has four ADC pins with a resolution of 12 Bits and a maximum sampling frequency of 500 KHz.\u00a0<\/p><p>The ADC is configured in \u201cone-shot\u201d mode, meaning it gives us a sample as soon as we request it.\u00a0<\/p><p>The peripheral timer is set to generate an interrupt at a frequency similar to the ADC sampling rate. Therefore, the interrupt service routine (ISR) is responsible for sampling the received signal from the microphone and storing the data in an audio buffer.<\/p><p>Since the maximum ADC frequency is 500 KHz, the minimum time between two consecutive conversions will be 2\u00b5s. This won\u2019t pose a problem for us because we take samples from the voice signal at 16 KHz.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1d90f66 elementor-widget elementor-widget-heading\" data-id=\"1d90f66\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Programming Raspberry Pi Pico with PlatformIO<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f41d4da elementor-widget elementor-widget-text-editor\" data-id=\"f41d4da\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Before entering the PlatformIO software, open Arduino IDE and search for \u201crp2040 mbed\u201d at Tools-&gt;Board-&gt;Boards manager. Then, select the desired version and click on \u201cInstall.\u201d Wait for the installation process to finish. Finally, close Arduino IDE.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-28f93e6 elementor-widget elementor-widget-image\" data-id=\"28f93e6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Install-lib.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-Install-lib\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODU1IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1JbnN0YWxsLWxpYi5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Install-lib-1200x750.jpg\" class=\"attachment-large size-large wp-image-28855\" alt=\"select the desired version and click on \u201cInstall.\u201d Wait for the installation process to finish. Finally, close Arduino IDE\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Install-lib-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Install-lib-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96efcf6 elementor-alert-warning elementor-widget elementor-widget-alert\" data-id=\"96efcf6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"alert.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-alert\" role=\"alert\">\n\n\t\t\t\t\t\t<span class=\"elementor-alert-title\">Warning<\/span>\n\t\t\t\n\t\t\t\t\t\t<span class=\"elementor-alert-description\">Codes that use the Edge Impulse library cannot be programmed on your board with Arduino IDE because the length of the file addresses used in the code goes beyond what Windows can handle. There are two ways to solve this issue:<\/span>\n\t\t\t\n\t\t\t\t\t\t<button type=\"button\" class=\"elementor-alert-dismiss\" aria-label=\"Dismiss this alert.\">\n\t\t\t\t\t\t\t\t\t<span aria-hidden=\"true\">&times;<\/span>\n\t\t\t\t\t\t\t<\/button>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f34a30f elementor-widget elementor-widget-text-editor\" data-id=\"f34a30f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Upload code with Arduino IDE in Linux environment<\/li><li>Use PlatformIO software<\/li><\/ul><p>PlatformIO software is one of the extensions of Visual Studio Code.<br \/>You can download and install Visual Studio Code from this link.<br \/>After installing and running the software, go to the &#8220;Extensions&#8221; section (Ctrl+Shift+X) and enter the term &#8220;PlatformIO&#8221; in the search field.<br \/>After installation, follow the steps below:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-704e698 elementor-widget elementor-widget-text-editor\" data-id=\"704e698\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Create a new project.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6b47c3c elementor-widget elementor-widget-image\" data-id=\"6b47c3c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-1.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 1\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODU5IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tMS5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-1-1200x750.jpg\" class=\"attachment-large size-large wp-image-28859\" alt=\"Create a new project.\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-1-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-1-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6c81b99 elementor-widget elementor-widget-text-editor\" data-id=\"6c81b99\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Click on &#8220;New Project.&#8221;<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2e9b7ff elementor-widget elementor-widget-image\" data-id=\"2e9b7ff\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-2.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 2\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODYwIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tMi5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-2-1200x750.jpg\" class=\"attachment-large size-large wp-image-28860\" alt=\"click new project\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-2-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-2-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-afc456c elementor-widget elementor-widget-text-editor\" data-id=\"afc456c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Specify the project name, board type, and framework.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f06df8a elementor-widget elementor-widget-image\" data-id=\"f06df8a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-3.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 3\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODYxIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tMy5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-3-1200x750.jpg\" class=\"attachment-large size-large wp-image-28861\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-3-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-3-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-67a4548 elementor-widget elementor-widget-text-editor\" data-id=\"67a4548\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The files related to your project are placed in the Documents folder by default.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ff2bc3d elementor-widget elementor-widget-image\" data-id=\"ff2bc3d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-4.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 4\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODYyIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tNC5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-4-1200x750.jpg\" class=\"attachment-large size-large wp-image-28862\" alt=\"The files related to your project are placed in the Documents folder by default\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-4-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-4-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b5795ef elementor-widget elementor-widget-text-editor\" data-id=\"b5795ef\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Install the trained model library<\/li><\/ul><p>Now unzip the model library file you downloaded and copy the contents of the \u201csrc\u201d folder to the following path: Documents-&gt;PlatformIO-&gt;YOUR PROJECT NAME-&gt;src<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1eacf7b elementor-widget elementor-widget-image\" data-id=\"1eacf7b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2024\/04\/Voice-recog-RPI-pico-PIO-5.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 5\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6MjkzODgsInVybCI6Imh0dHBzOlwvXC9lbGVjdHJvcGVhay5jb21cL2xlYXJuXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDI0XC8wNFwvVm9pY2UtcmVjb2ctUlBJLXBpY28tUElPLTUuanBnIn0%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2024\/04\/Voice-recog-RPI-pico-PIO-5-1200x750.jpg\" class=\"attachment-large size-large wp-image-29388\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2024\/04\/Voice-recog-RPI-pico-PIO-5-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2024\/04\/Voice-recog-RPI-pico-PIO-5-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8fdfc3d elementor-widget elementor-widget-text-editor\" data-id=\"8fdfc3d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Enter the program code<\/li><\/ul><p>Go back to PlatformIO and open the main.cpp file from the src folder.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ccce0e5 elementor-widget elementor-widget-image\" data-id=\"ccce0e5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-6.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 6\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODY1IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tNi5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-6-1200x750.jpg\" class=\"attachment-large size-large wp-image-28865\" alt=\"Go back to PlatformIO and open the main.cpp file from the src folder\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-6-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-6-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4cd2942 elementor-widget elementor-widget-text-editor\" data-id=\"4cd2942\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Now copy the following code into it.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5f15e49 elementor-widget elementor-widget-html\" data-id=\"5f15e49\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<pre class=\"line-numbers lang-arduino\"><code>\r\n\/*   \r\nmodified on Aug 2, 2023\r\nModified by Majid Merati from https:\/\/github.com\/PacktPublishing\/TinyML-Cookbook\/blob\/main\/Chapter04\/ArduinoSketches\/09_kws_raspberrypi_pico.ino\r\nhttps:\/\/electropeak.com\/learn\/ \r\n*\/ \r\n\r\n#include \"mbed.h\"\r\n#include \"hardware\/adc.h\"\r\n\r\n\/\/ If your target is limited in memory remove this macro to save 10K RAM\r\n#define EIDSP_QUANTIZE_FILTERBANK   0\r\n\r\n\/* Includes ---------------------------------------------------------------- *\/\r\n#include &lt;YesOrNo_inferencing.h&gt;\r\n\r\n#define ON          1\r\n#define OFF         0\r\n#define PRESSED     0\r\n#define LEDR        p9\r\n#define LEDG        p8\r\n#define LEDB        p7\r\n#define LED_BUILTIN p25\r\n#define BUTTON      p10\r\n#define BIAS_MIC    1552 \/\/ (1.25V * 4095) \/ 3.3\r\n#define AUDIO_SAMPLING_RATE 16000.0\r\n#define NUM_YesOrNo  3\r\n#define PROBABILITY_THR 0.5\r\n#define GAIN        1\r\n\r\nstatic mbed::Ticker     timer;\r\nstatic mbed::DigitalOut led_builtin(LED_BUILTIN);\r\nstatic mbed::DigitalIn  button(BUTTON);\r\n\r\n\/** Audio buffers, pointers and selectors *\/\r\ntypedef struct {\r\n    int16_t *buffer;\r\n    int16_t *buffer_filtered;\r\n    uint8_t buf_ready;\r\n    uint32_t buf_count;\r\n    uint32_t n_samples;\r\n} inference_t;\r\n\r\nstatic volatile inference_t inference;\r\nstatic bool debug_nn = false;\r\nstatic bool debug_audio_raw = true;\r\nstatic bool test_leds = false; \/\/ Set this to true to test the LEDs\r\n\r\nstatic volatile int  ix_buffer       = 0;\r\nstatic volatile bool is_buffer_ready = false;\r\n\r\nstatic void adc_setup() {\r\n  adc_init();\r\n  adc_gpio_init(26);\r\n  adc_select_input(0);\r\n}\r\n\r\nstatic void print_raw_audio() {\r\n  for(int i = 0; i &lt; EI_CLASSIFIER_RAW_SAMPLE_COUNT; ++i) {\r\n    ei_printf(\"%d\\n\", inference.buffer[i]);\r\n  }\r\n}\r\n\r\nvoid timer_ISR() {\r\n  if(ix_buffer &lt; EI_CLASSIFIER_RAW_SAMPLE_COUNT) {\r\n    int16_t v = (int16_t)((adc_read() - BIAS_MIC)) * GAIN;\r\n    inference.buffer[ix_buffer++] = (int16_t)v;\r\n  }\r\n  else {\r\n    is_buffer_ready = true;\r\n  }\r\n}\r\n\r\n\/**\r\n * @brief      Printf function uses vsnprintf and output using Arduino Serial\r\n *\r\n * @param[in]  format     Variable argument list\r\n *\/\r\nvoid ei_printf(const char *format, ...) {\r\n  static char print_buf[1024] = { 0 };\r\n\r\n  va_list args;\r\n  va_start(args, format);\r\n  int r = vsnprintf(print_buf, sizeof(print_buf), format, args);\r\n  va_end(args);\r\n\r\n  if (r &gt; 0) {\r\n      Serial.write(print_buf);\r\n  }\r\n}\r\n\r\n\/**\r\n * @brief      Init inferencing struct and setup\/start PDM\r\n *\r\n * @param[in]  n_samples  The n samples\r\n *\r\n * @return     { description_of_the_return_value }\r\n *\/\r\nstatic bool microphone_inference_start(uint32_t n_samples) {\r\n  inference.buffer = (int16_t *)malloc(n_samples * sizeof(int16_t));\r\n\r\n  if(inference.buffer == NULL) {\r\n      return false;\r\n  }\r\n\r\n  inference.buf_count  = 0;\r\n  inference.n_samples  = n_samples;\r\n  inference.buf_ready  = 0;\r\n\r\n  return true;\r\n}\r\n\r\n\/**\r\n * @brief      Wait on new data\r\n *\r\n * @return     True when finished\r\n *\/\r\nstatic bool microphone_inference_record(void) {\r\n  unsigned int sampling_period_us = 1000000 \/ 16000;\r\n\r\n  ix_buffer = 0;\r\n  is_buffer_ready = false;\r\n  led_builtin = ON;\r\n  timer.attach_us(&amp;timer_ISR, sampling_period_us);\r\n\r\n  while(!is_buffer_ready);\r\n\r\n  timer.detach();\r\n  led_builtin = OFF;\r\n\r\n  if(debug_audio_raw) {\r\n    print_raw_audio();\r\n  }\r\n\r\n  return true;\r\n}\r\n\r\n\/**\r\n * Get raw audio signal data\r\n *\/\r\nstatic int microphone_audio_signal_get_data(size_t offset, size_t length, float *out_ptr) {\r\n    numpy::int16_to_float(&amp;inference.buffer[offset], out_ptr, length);\r\n\r\n    return 0;\r\n}\r\n\r\nstatic void microphone_inference_end(void) {\r\n  free(inference.buffer);\r\n}\r\n\r\n#if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_MICROPHONE\r\n#error \"Invalid model for current sensor.\"\r\n#endif\r\n\r\n\/** \r\n * @brief      Arduino setup function\r\n *\/\r\nvoid setup()\r\n{\r\n  Serial.begin(115200);\r\n\r\n  while(!Serial);\r\n\r\n  adc_setup();\r\n\r\n  led_builtin = 0;\r\n\r\n  button.mode(PullUp);\r\n\r\n  if (microphone_inference_start(EI_CLASSIFIER_RAW_SAMPLE_COUNT) == false) {\r\n      ei_printf(\"ERR: Failed to setup audio sampling\\r\\n\");\r\n      return;\r\n  }\r\n}\r\n\r\n\/**\r\n * @brief      Arduino main function. Runs the inferencing loop.\r\n *\/\r\nvoid loop()\r\n{\r\n  if(button == PRESSED) {\r\n    delay(700);\r\n\r\n    bool m = microphone_inference_record();\r\n    if (!m) {\r\n        ei_printf(\"ERR: Failed to record audio...\\n\");\r\n        return;\r\n    }\r\n\r\n    signal_t signal;\r\n    signal.total_length = EI_CLASSIFIER_RAW_SAMPLE_COUNT;\r\n    signal.get_data = &amp;microphone_audio_signal_get_data;\r\n    ei_impulse_result_t result = { 0 };\r\n\r\n    EI_IMPULSE_ERROR r = run_classifier(&amp;signal, &amp;result, debug_nn);\r\n    if (r != EI_IMPULSE_OK) {\r\n        ei_printf(\"ERR: Failed to run classifier (%d)\\n\", r);\r\n        return;\r\n    }\r\n\r\n    \/\/ print the predictions\r\n    ei_printf(\"Predictions \");\r\n    ei_printf(\"(DSP: %d ms., Classification: %d ms., Anomaly: %d ms.)\",\r\n        result.timing.dsp, result.timing.classification, result.timing.anomaly);\r\n    ei_printf(\": \\n\");\r\n    for (size_t ix = 0; ix &lt; EI_CLASSIFIER_LABEL_COUNT; ix++) {\r\n        ei_printf(\"    %s: %.5f\\n\", result.classification[ix].label, result.classification[ix].value);\r\n    }\r\n\r\n    \/\/ Get the index with higher probability\r\n    size_t ix_max = 0;\r\n    float  pb_max = 0;\r\n    for (size_t ix = 0; ix &lt; EI_CLASSIFIER_LABEL_COUNT; ix++) {\r\n      if(result.classification[ix].value &gt; pb_max) {\r\n        ix_max = ix;\r\n        pb_max = result.classification[ix].value;\r\n      }\r\n    }\r\n\r\n   if(pb_max &gt; PROBABILITY_THR) {\r\n      switch (ix_max){\r\n        case 0:\r\n        \/\/YOU CAN ADD YOUR FUNCTION HERE\r\n        break;\r\n        case 1:\r\n        \/\/YOU CAN ADD YOUR FUNCTION HERE\r\n        break;\r\n        case 2:\r\n        \/\/YOU CAN ADD YOUR FUNCTION HERE\r\n        break;\r\n        default:\r\n          ei_printf(\"Error! operator is not correct\");\r\n      }\r\n\r\n    while(button == PRESSED);\r\n    delay(1000);\r\n  }\r\n}\r\n\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3dfff26 elementor-widget elementor-widget-text-editor\" data-id=\"3dfff26\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>After you&#8217;ve copied the code, just give it a moment for the C++ compiler to do a quick check. You&#8217;ll see that there are some errors in the code. The code lines marked with a red line underneath them are the ones that the compiler says have errors.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7c7e38d elementor-widget elementor-widget-image\" data-id=\"7c7e38d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-7.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 7\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODY5IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tNy5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-7-1200x750.jpg\" class=\"attachment-large size-large wp-image-28869\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-7-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-7-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-246025c elementor-widget elementor-widget-text-editor\" data-id=\"246025c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>To resolve these issues, follow these steps:<\/p><ul><li>Click on the search window, press the F1 key on your keyboard, and open the \u201cC\/C++: Edit Configurations (JSON)\u201d file. Once the file is open, delete the written codes.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1ca562d elementor-widget elementor-widget-image\" data-id=\"1ca562d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-8.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 8\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODcwIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tOC5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-8-1200x750.jpg\" class=\"attachment-large size-large wp-image-28870\" alt=\"delete the written codes\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-8-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-8-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-95f5338 elementor-widget elementor-widget-text-editor\" data-id=\"95f5338\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Modify the library addresses: Copy the following code into this file.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c545384 elementor-widget elementor-widget-html\" data-id=\"c545384\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<pre class=\"line-numbers lang-arduino\"><code>\r\n\/\/\r\n\/\/ !!! WARNING !!! AUTO-GENERATED FILE!\r\n\/\/ PLEASE DO NOT MODIFY IT AND USE \"platformio.ini\":\r\n\/\/ https:\/\/docs.platformio.org\/page\/projectconf\/section_env_build.html#build-flags\r\n\/\/\r\n{\r\n    \"configurations\": [\r\n        {\r\n            \"name\": \"PlatformIO\",\r\n            \"includePath\": [\r\n                \"c:\/Users\/Caferobot9\/Documents\/PlatformIO\/Projects\/YesOrNo3\/include\",\r\n                \"c:\/Users\/Caferobot9\/Documents\/PlatformIO\/Projects\/YesOrNo3\/src\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/cores\/arduino\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/cores\/arduino\/api\/deprecated\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/cores\/arduino\/api\/deprecated-avr-comp\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/variants\/RASPBERRY_PI_PICO\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/Camera\/src\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/Ethernet\/src\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/GC2145\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/GPS\/src\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/GSM\/src\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/Himax_HM01B0\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/Himax_HM0360\",\r\n                \"C:\/Users\/Caferobot9\/.platformio\/packages\/framework-arduino-mbed\/libraries\/KernelDebug\/src\",\r\n                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\"DEVICE_PWMOUT=1\",\r\n                \"DEVICE_RESET_REASON=1\",\r\n                \"DEVICE_RTC=1\",\r\n                \"DEVICE_SERIAL=1\",\r\n                \"DEVICE_SERIAL_FC=1\",\r\n                \"DEVICE_SPI=1\",\r\n                \"DEVICE_USBDEVICE=1\",\r\n                \"DEVICE_USTICKER=1\",\r\n                \"DEVICE_WATCHDOG=1\",\r\n                \"MBEDTLS_ENTROPY_NV_SEED\",\r\n                \"MBED_BUILD_TIMESTAMP=1670863580.9430058\",\r\n                \"MBED_MPU_CUSTOM\",\r\n                \"PICO_NO_BINARY_INFO=1\",\r\n                \"PICO_ON_DEVICE=1\",\r\n                \"PICO_RP2040_USB_DEVICE_ENUMERATION_FIX=1\",\r\n                \"PICO_TIME_DEFAULT_ALARM_POOL_DISABLED\",\r\n                \"PICO_UART_ENABLE_CRLF_SUPPORT=0\",\r\n                \"TARGET_CORTEX\",\r\n                \"TARGET_CORTEX_M\",\r\n                \"TARGET_LIKE_CORTEX_M0\",\r\n                \"TARGET_LIKE_MBED\",\r\n                \"TARGET_M0P\",\r\n                \"TARGET_NAME=RASPBERRY_PI_PICO\",\r\n                \"TARGET_RASPBERRYPI\",\r\n                \"TARGET_RASPBERRY_PI_PICO\",\r\n                \"TARGET_RELEASE\",\r\n                \"TARGET_RP2040\",\r\n                \"TARGET_memmap_default\",\r\n                \"TOOLCHAIN_GCC\",\r\n                \"TOOLCHAIN_GCC_ARM\",\r\n                \"__CMSIS_RTOS\",\r\n                \"__CORTEX_M0PLUS\",\r\n                \"__MBED_CMSIS_RTOS_CM\",\r\n                \"__MBED__=1\",\r\n                \"MBED_NO_GLOBAL_USING_DIRECTIVE=1\",\r\n                \"CORE_MAJOR=\",\r\n                \"CORE_MINOR=\",\r\n                \"CORE_PATCH=\",\r\n                \"USE_ARDUINO_PINOUT\",\r\n                \"ARDUINO=10810\",\r\n                \"ARDUINO_ARCH_MBED\",\r\n                \"\"\r\n            ],\r\n            \"cStandard\": \"gnu11\",\r\n            \"cppStandard\": \"gnu++14\",\r\n            \"compilerPath\": \"C:\/Users\/Caferobot9\/.platformio\/packages\/toolchain-gccarmnoneeabi\/bin\/arm-none-eabi-gcc.exe\",\r\n            \"compilerArgs\": [\r\n                \"-mcpu=cortex-m0plus\",\r\n                \"-mthumb\",\r\n                \"-iprefixC:UsersCaferobot9.platformiopackagesframework-arduino-mbedcoresarduino\",\r\n                \"@C:UsersCaferobot9.platformiopackagesframework-arduino-mbedvariantsRASPBERRY_PI_PICOincludes.txt\",\r\n                \"\"\r\n            ]\r\n        }\r\n    ],\r\n    \"version\": 4\r\n}\r\n\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-86e8f96 elementor-widget elementor-widget-text-editor\" data-id=\"86e8f96\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Select the word &#8220;Caferobot9&#8221; and press Ctrl+H on your keyboard. Then, type in your username in the section labeled &#8220;YOUR USER NAME HERE&#8221; and click on &#8220;Replace All.&#8221;<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f7e58f5 elementor-widget elementor-widget-image\" data-id=\"f7e58f5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-9.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 9\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODc0IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tOS5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-9-1200x750.jpg\" class=\"attachment-large size-large wp-image-28874\" alt=\"\u2022 Select the word &quot;Caferobot9&quot; and press Ctrl+H on your keyboard. Then, type in your username in the section labeled &quot;YOUR USER NAME HERE&quot; and click on &quot;Replace All.&quot;\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-9-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-9-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-333ab81 elementor-widget elementor-widget-text-editor\" data-id=\"333ab81\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>You can find your exact username in Windows from: \u201cC:\\Users\u201d<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c5c9d43 elementor-alert-info elementor-widget elementor-widget-alert\" data-id=\"c5c9d43\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"alert.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-alert\" role=\"alert\">\n\n\t\t\t\t\t\t<span class=\"elementor-alert-title\">TIP<\/span>\n\t\t\t\n\t\t\t\t\t\t<span class=\"elementor-alert-description\">Between lines 222 and 235 of the code, you can define your commands for each class (Yes, No, and Undefined). These categories are defined by numbers. For example, you can turn on or off one of the pins on Raspberry Pi Pico.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-79ef17e elementor-widget elementor-widget-text-editor\" data-id=\"79ef17e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>After doing this, give the compiler a few moments to perform the necessary operations. Then click on &#8220;Build&#8221; at the bottom of the page.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c561f5 elementor-widget elementor-widget-image\" data-id=\"3c561f5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-10.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 10\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODc1IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tMTAuanBnIn0%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-10-1200x750.jpg\" class=\"attachment-large size-large wp-image-28875\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-10-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-10-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fbcee2f elementor-widget elementor-widget-text-editor\" data-id=\"fbcee2f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>If you have followed the steps correctly, you will see the following phrases in the output.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0ef0dda elementor-widget elementor-widget-image\" data-id=\"0ef0dda\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-11.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 11\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODc2IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tMTEuanBnIn0%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-11-1200x750.jpg\" class=\"attachment-large size-large wp-image-28876\" alt=\"you will see the following phrases in the output\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-11-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-11-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fb31c25 elementor-widget elementor-widget-text-editor\" data-id=\"fb31c25\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Next, connect your Raspberry Pi board to the computer while holding down the &#8220;BOOT&#8221; button.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f443cb7 elementor-widget elementor-widget-image\" data-id=\"f443cb7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-BOOTSEL-button.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-BOOTSEL-button\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODc3IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1CT09UU0VMLWJ1dHRvbi5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-BOOTSEL-button-1200x750.jpg\" class=\"attachment-large size-large wp-image-28877\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-BOOTSEL-button-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-BOOTSEL-button-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2d7a80c elementor-widget elementor-widget-text-editor\" data-id=\"2d7a80c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Finally, click on the \u201cUpload\u201d button to program your Raspberry Pi Pico board.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-94c9d57 elementor-widget elementor-widget-image\" data-id=\"94c9d57\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-12.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-PIO 12\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODc4IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1QSU8tMTIuanBnIn0%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-12-1200x750.jpg\" class=\"attachment-large size-large wp-image-28878\" alt=\"click on the \u201cUpload\u201d button to program your Raspberry Pi Pico board\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-12-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-PIO-12-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f4b973c elementor-widget elementor-widget-text-editor\" data-id=\"f4b973c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Now, open the Arduino IDE software and select the correct port. After that, open the Serial monitor.<\/p><p>Then press the button connected to the GP10 pin of Raspberry Pi Pico. Here, you\u2019ll notice that the LED on the Raspberry Pi board turns on, and after 1 second, it turns off. During this time, if you say the words &#8220;Yes&#8221; or &#8220;No,&#8221; you\u2019ll see the following responses on the serial monitor, respectively.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f3371e6 elementor-widget elementor-widget-image\" data-id=\"f3371e6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-2.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-result 2\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODc5IiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1yZXN1bHQtMi5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-2-1200x750.jpg\" class=\"attachment-large size-large wp-image-28879\" alt=\"\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-2-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-2-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ba87b64 elementor-widget elementor-widget-image\" data-id=\"ba87b64\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-3.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-result 3\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODgwIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1yZXN1bHQtMy5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-3-1200x750.jpg\" class=\"attachment-large size-large wp-image-28880\" alt=\"Voice recognition RPI pico result\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-3-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-result-3-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8690fc2 elementor-widget elementor-widget-text-editor\" data-id=\"8690fc2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Also, if you open the Serial Plotter port and do this, the voice signal sensed by the microphone will be displayed.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb9ff6c elementor-widget elementor-widget-image\" data-id=\"eb9ff6c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Serial-Plotter.jpg\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"Voice-recog-RPI-pico-Serial-Plotter\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6IjI4ODgxIiwidXJsIjoiaHR0cHM6XC9cL2VsZWN0cm9wZWFrLmNvbVwvbGVhcm5cL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjNcLzEyXC9Wb2ljZS1yZWNvZy1SUEktcGljby1TZXJpYWwtUGxvdHRlci5qcGcifQ%3D%3D\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"713\" src=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Serial-Plotter-1200x750.jpg\" class=\"attachment-large size-large wp-image-28881\" alt=\"the voice signal sensed by the microphone will be displayed\" srcset=\"https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Serial-Plotter-600x375.jpg 600w, https:\/\/electropeak.com\/learn\/wp-content\/uploads\/2023\/12\/Voice-recog-RPI-pico-Serial-Plotter-768x480.jpg 768w\" sizes=\"(max-width: 1140px) 100vw, 1140px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-34208a0 elementor-widget elementor-widget-heading\" data-id=\"34208a0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What\u2019s Next?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8231a35 elementor-widget elementor-widget-text-editor\" data-id=\"8231a35\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In this tutorial, you first became familiar with the concept of AI and machine learning. Next, using the attractive graphical interface of Edge Impulse, you created a model to detect keywords. Finally, you successfully ran the model on Raspberry Pi Pico.<\/p><p>Machine learning enables you to perform various tasks without the need for complex calculations. Some of them include:<\/p><p><b>1- Sensor fusion:<\/b><\/p><p>In some projects, we can use multiple sensors to measure various parameters to gather up-to-date information. For example, by using temperature, humidity, light, and pressure sensors, you can determine the present weather conditions. With more advanced technology, you can even predict the weather.<\/p><p>In the past, we\u2019d use heavy computational codes to achieve this goal, requiring powerful hardware. But nowadays, you can do this task much more easily by using machine learning to combine data.<\/p><p><b>2- Object detection in images:<\/b><\/p><p>Without the use of our eyes and the ability to perceive images, many everyday activities would be impossible for humans. Images contain a vast amount of information based on which, the human brain sends commands to the body. Therefore, image processing has a wide range of applications.<\/p><p>By extracting key points from images containing the desired objects and creating a model based on them, you can have an object detection system according to your needs. This technology has various applications: license plate recognition, population counting, traffic control, image-to-text conversion, etc.<\/p><p>\u00a0<\/p><p><b>3- Recognizing gestures and motion patterns:<\/b><\/p><p>In the field of medicine, especially physiotherapy, robots have been invented to help humans in improving their physical abilities. You can accurately monitor the movements of various body parts by using motion sensors like the gyroscope, accelerometer, and magnetometer, along with neural sensors. If you create a model for each movement such as sitting, standing up, walking, running, etc., you can implement this model using an inexpensive microcontroller.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Introduction Welcome to the world of innovation with Raspberry Pi Pico! This article explores voice recognition and wake word detection using machine learning techniques. Discover how to leverage Raspberry Pi Pico&#8217;s capabilities to create intelligent devices that respond to voice commands. Join us as we explore the exciting possibilities for smart home technology, robotics, and [&hellip;]<\/p>\n","protected":false},"author":29,"featured_media":28807,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[946,947,948],"tags":[],"platform":[1072],"bytype":[1074],"difficulty":[1079],"related_products":[],"class_list":["post-28805","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-home-automation","category-programming","platform-raspberry-pi","bytype-diy-projects","difficulty-advanced"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Raspberry Pi Pico Voice Recognition And Wake Word Using AI<\/title>\n<meta name=\"description\" content=\"Discover the power of Raspberry Pi Pico voice recognition! Learn how to implement voice recognition and wake word detection in this guide.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/electropeak.com\/learn\/raspberry-pi-pico-voice-recognition-and-wake-word-using-ai\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Raspberry Pi Pico Voice Recognition And Wake Word Using AI\" \/>\n<meta property=\"og:description\" content=\"Discover the power of Raspberry Pi Pico voice recognition! 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