Building a Speech-to-Text Application with Whisper and React Native
In this article, we’ll explore how to create a speech-to-text application using Whisper, a powerful speech recognition model, and React Native. We’ll cover the setup of Whisper, the creation of a backend application with Flask, and the development of a mobile client with React Native.
What is Speech Recognition?
Speech recognition is the process of converting spoken language into text. It’s a complex task that requires sophisticated algorithms and machine learning models. Whisper is one such model that has gained popularity in recent times due to its high accuracy and ease of use.
What is Whisper?
Whisper is a pre-trained speech recognition model that can be fine-tuned for specific tasks. It’s based on a sequence-to-sequence architecture and uses a combination of convolutional and recurrent neural networks to recognize speech patterns. Whisper is particularly useful for building speech-to-text applications, as it can handle a wide range of accents and speaking styles.
Setting up Whisper
To use Whisper, we need to set up a backend application that can receive audio inputs and send them to the Whisper model for processing. We’ll use Flask, a popular Python web framework, to build our backend application.
Creating a Backend Application with Flask
First, we need to install Flask and create a new project. We’ll also need to install the ffmpeg library, which is required for audio processing.
bash
pip install flask ffmpeg
Next, we’ll create a new file called app.py and add the following code:
“`python
from flask import Flask, request, jsonify
import whisper
app = Flask(name)
@app.route(‘/transcribe’, methods=[‘POST’])
def transcribe():
audiodata = request.getjson()[‘audio’]
model = whisper.loadmodel(‘base’)
result = model.transcribe(audiodata)
return jsonify({‘text’: result[‘text’]})
if name == ‘main‘:
app.run(debug=True)
“
This code creates a Flask application that listens for POST requests to the
Creating a Mobile Client with React Native
Now that we have our backend application up and running, we can start building our mobile client with React Native. We’ll use the expo-av library to handle audio recording and playback.
bash
npm install expo-av
Next, we’ll create a new file called App.js and add the following code:
“`jsx
import React, { useState } from ‘react’;
import { View, Text, Button } from ‘react-native’;
import { Audio } from ‘expo-av’;
const App = () => {
const [recording, setRecording] = useState(false);
const [transcribedText, setTranscribedText] = useState(”);
const startRecording = async () => {
setRecording(true);
const audio = new Audio.Recording();
await audio.prepareToRecordAsync();
await audio.startAsync();
};
const stopRecording = async () => {
setRecording(false);
const audio = new Audio.Recording();
await audio.stopAndUnloadAsync();
const audioData = await audio.getURIAsync();
const response = await fetch(‘http://localhost:5000/transcribe’, {
method: ‘POST’,
headers: { ‘Content-Type’: ‘application/json’ },
body: JSON.stringify({ audio: audioData }),
});
const result = await response.json();
setTranscribedText(result.text);
};
return (
);
};
export default App;
“`
This code creates a simple React Native application that allows users to record and transcribe audio. When the user starts recording, the application sends a POST request to our backend application with the audio data. When the user stops recording, the application receives the transcribed text from our backend application and displays it on the screen.
Conclusion
In this article, we’ve learned how to build a speech-to-text application using Whisper and React Native. We’ve covered the setup of Whisper, the creation of a backend application with Flask, and the development of a mobile client with React Native. With this knowledge, you can build your own speech-to-text applications and explore the many possibilities of speech recognition technology.