Speech Command Recognition With Tensorflow.JS and React.JS

Introduction

In this article, we will explore how to build a speech command recognition application using Tensorflow.js and React.js. By leveraging the TensorFlow.js speech command recognition model, we can create a web app that responds to various voice commands in real-time. The purpose of this tutorial is to guide you through the entire process, from setting up your React environment to implementing the real-time speech recognition functionality.

Getting Started

Prerequisites

To follow along with this tutorial, you should have Node.js and npm installed on your machine. Familiarity with React.js will also be helpful, though not strictly necessary.

Setting Up the React App

Create a New React App: Open a command prompt or terminal and use the create-react-app command:
```
npx create-react-app speech-rec
```
This command sets up a new React application in a folder named speech-rec.
Navigate to the App Directory: Change into the newly created directory:
```
cd speech-rec
```
Open the App in Your Code Editor: For instance, if you are using Visual Studio Code:
```
code .
```
Start the App: Run the following command to bring up your application in the browser:
```
npm start
```

Installing TensorFlow.js Dependencies

Next, we need to install the necessary TensorFlow.js packages. In the terminal, run:

npm install @tensorflow/tfjs @tensorflow-models/speech-commands

This command installs the TensorFlow.js library and the speech command recognition model.

Implementing Speech Command Recognition

Importing Dependencies

Open the App.js file in your text editor and import the required dependencies at the top:

import React, ( useEffect, useState ) from "react";
import * as tf from "@tensorflow/tfjs";
import * as speech from "@tensorflow-models/speech-commands";

Setting Up State Variables

Create states to store the TensorFlow model, recognized action, and labels for commands:

const [model, setModel] = useState(null);
const [action, setAction] = useState("");
const [labels, setLabels] = useState([]);

Loading the Speech Command Model

Define an asynchronous function loadModel that initializes the speech command model and retrieves the word labels:

const loadModel = async () => (
  const recognizer = await speech.create("BROWSER_FFT");
  setModel(recognizer);
  await recognizer.ensureModelLoaded();
  setLabels(recognizer.wordLabels());
);

Call this function in a useEffect hook to ensure it runs once when the component mounts:

useEffect(() => (
  loadModel();
), []);

Recognizing Commands

Create a function recognizeCommands that listens for voice commands and processes the results:

const recognizeCommands = async () => (
  if (!model) return;
  model.listen(({ scores )) => (
    const commandIndex = argMax(scores);
    setAction(labels[commandIndex]);
  ));
};

Add a button in your component's return statement to trigger recognition:

<button onClick=(recognizeCommands)>Listen for Commands</button>
<div>(action || "No action detected.")</div>

Displaying Results

After detecting a command, the app will display it on the screen, while also logging it to the console for debugging.

Running the Application

After implementing the above functions and code, start your React application and check the console to verify that the commands are being recognized correctly. Speak different commands to see if they show up on the UI.

Conclusion

By following these steps, you now have a functional speech command recognition application built with Tensorflow.js and React.js. You can experiment with different commands and even expand on this foundation to create more complex applications.

Keywords

TensorFlow.js
Speech Command Recognition
React.js
JavaScript
Web Application
Machine Learning
Microphone Input
Real-time Processing

FAQ

Q: What is TensorFlow.js?
A: TensorFlow.js is an open-source library for machine learning in JavaScript. It enables the use of machine learning models in web applications.

Q: Which speech commands can be recognized by the model?
A: The model can recognize various specific commands such as "up," "down," "left," "right," numbers, and more.

Q: Do I need prior knowledge of React to follow this tutorial?
A: While some familiarity with React can be helpful, this tutorial is structured to guide beginners through the implementation process.

Q: Can I extend the application to recognize custom commands?
A: Yes! You can refine the model and train it to recognize additional commands or even your own custom commands.

Q: How does the microphone input work in this application?
A: The application uses the Web Audio API through TensorFlow.js to capture and analyze audio input from the user's microphone in real time.

Speech Command Recognition With Tensorflow.JS and React.JS | Javascript AI