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How to implement an online speech recognition system using WebSocket and JavaScript
How to implement an online speech recognition system using WebSocket and JavaScript
Dec 17, 2023 pm 02:54 PM
How to use WebSocket and JavaScript to implement an online speech recognition system
Introduction:
With the continuous development of science and technology, speech recognition technology has become an important part of the field of artificial intelligence. An important part of. The online speech recognition system based on WebSocket and JavaScript has the characteristics of low latency, real-time and cross-platform, and has become a widely used solution. This article will introduce how to use WebSocket and JavaScript to implement an online speech recognition system, and provide specific code examples to help readers better understand and apply this technology.
1. Introduction to WebSocket:
WebSocket is a protocol for full-duplex communication on a single TCP connection and can be used for real-time data transmission between the client and the server. Compared with the HTTP protocol, WebSocket has the advantages of low latency and real-time performance, and can solve the high delay and resource waste problems caused by HTTP long polling. It is very suitable for application scenarios with high real-time requirements.
2. Overview of speech recognition technology:
Speech recognition technology refers to the process by which computers convert human voice information into understandable text or commands. It is an important research direction in the fields of natural language processing and artificial intelligence, and is widely used in intelligent assistants, voice interaction systems, speech transcription and other fields. Currently, there are many open source speech recognition engines, such as Google's Web Speech API and CMU Sphinx. We can implement online speech recognition systems based on these engines.
3. Online speech recognition system implementation steps:
-
Create WebSocket connection:
In JavaScript code, you can use the WebSocket API to establish a WebSocket connection with the server . The specific code examples are as follows:var socket = new WebSocket("ws://localhost:8080"); // 這里的地址需要根據(jù)實(shí)際情況做修改 Initialize the speech recognition engine:
Select the appropriate speech recognition engine according to actual needs and initialize the engine. Here we take Google's Web Speech API as an example. The specific code examples are as follows:var recognition = new webkitSpeechRecognition(); recognition.continuous = true; // 設(shè)置為連續(xù)識別模式 recognition.interimResults = true; // 允許返回中間結(jié)果 recognition.lang = 'zh-CN'; // 設(shè)置識別語言為中文
Processing speech recognition results:
In the onmessage event callback function of WebSocket, process speech recognition The recognition results returned by the engine. Specific code examples are as follows:socket.onmessage = function(event) { var transcript = event.data; // 獲取識別結(jié)果 console.log("識別結(jié)果：" + transcript); // 在這里可以根據(jù)實(shí)際需求進(jìn)行具體的操作，如顯示在頁面上或者發(fā)送到后端進(jìn)行進(jìn)一步處理 };Start speech recognition:
Start the speech recognition process through the recognition.start method, and send audio data through WebSocket for real-time recognition. Specific code examples are as follows:recognition.onstart = function() { console.log("開始語音識別"); }; recognition.onresult = function(event) { var interim_transcript = ''; for (var i = event.resultIndex; i < event.results.length; ++i) { if (event.results[i].isFinal) { var final_transcript = event.results[i][0].transcript; socket.send(final_transcript); // 發(fā)送識別結(jié)果到服務(wù)器 } else { interim_transcript += event.results[i][0].transcript; } } }; recognition.start();Server-side processing:
On the server side, after receiving the audio data sent by the client, the corresponding speech recognition engine can be used for recognition. And return the recognition results to the client. Here we take Python's Flask framework as an example. The specific code examples are as follows:from flask import Flask, request app = Flask(__name__) @app.route('/', methods=['POST']) def transcribe(): audio_data = request.data # 使用語音識別引擎對音頻數(shù)據(jù)進(jìn)行識別 transcript = speech_recognition_engine(audio_data) return transcript if __name__ == '__main__': app.run(host='0.0.0.0', port=8080)
Summary:
This article introduces how to use WebSocket and JavaScript to implement an online speech recognition system, and provides Specific code examples. By using WebSocket to establish a real-time communication connection with the server and calling an appropriate speech recognition engine for real-time recognition, we can easily implement a low-latency, real-time online speech recognition system. I hope this article will be helpful to readers in understanding and applying this technology.
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