使用SpringBoot与WebSocket技术实现实时语音识别系统-工具盒子

本专题系统讲解了如何利用SpringBoot集成音频识别技术，涵盖了从基础配置到复杂应用的方方面面。通过本文，读者可以了解到在智能语音填单、智能语音交互、智能语音检索等场景中，音频识别技术如何有效提升人机交互效率。无论是本地存储检索，还是云服务的集成，丰富的应用实例为开发者提供了全面的解决方案。继续深入研究和实践这些技术，将有助于推动智能应用的广泛普及和发展，提升各类业务的智能化水平。

实时检测和识别的基本需求和技术难点

实时语音识别系统的基本需求是能够迅速准确地捕捉和转录用户的语音输入。以下是一些关键需求：

实时性：系统能够在语音输入的同时进行识别，尽量减少延迟。
准确性：高准确率的语音转文本识别，减少错误率。
可靠性：系统在高并发和不同网络环境下保持稳定运行。

技术难点主要包括：

音频流的实时传输：如何高效地将音频数据从客户端传输到服务器。
实时处理和识别：如何使用高效的算法在传输过程中对音频进行实时处理和识别。
系统延迟和性能优化：如何优化系统以减少延迟，尤其在高并发情况下。

使用SpringBoot与WebSocket技术实现实时语音识别

WebSocket是实现双向通信的理想技术选择，能够在客户端和服务器之间实现全双工通信。SpringBoot结合WebSocket可以方便地搭建实时语音识别系统。

1. 创建SpringBoot项目

首先，创建一个SpringBoot项目，并添加相关依赖：

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-websocket</artifactId>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
    <groupId>com.google.cloud</groupId>
    <artifactId>google-cloud-speech</artifactId>
    <version>1.22.8</version>
</dependency>

2. 配置WebSocket

定义WebSocket配置类，实现与客户端的通信：

import org.springframework.context.annotation.Configuration;
import org.springframework.web.socket.config.annotation.EnableWebSocket;
import org.springframework.web.socket.config.annotation.WebSocketConfigurer;
import org.springframework.web.socket.config.annotation.WebSocketHandlerRegistry;
@Configuration
@EnableWebSocket
public class WebSocketConfig implements WebSocketConfigurer {
    @Override
    public void registerWebSocketHandlers(WebSocketHandlerRegistry registry) {
        registry.addHandler(new AudioWebSocketHandler(), "/audio").setAllowedOrigins("*");
    }
}

3. 实现WebSocket处理器

处理WebSocket消息，包括接收音频数据流和发送识别结果：

import org.springframework.web.socket.BinaryMessage;
import org.springframework.web.socket.WebSocketSession;
import org.springframework.web.socket.handler.BinaryWebSocketHandler;
import com.google.cloud.speech.v1.*;
public class AudioWebSocketHandler extends BinaryWebSocketHandler {
    private SpeechClient speechClient;
    private StreamingRecognizeRequest.Builder requestBuilder;
    public AudioWebSocketHandler() {
        try {
            speechClient = SpeechClient.create();
            requestBuilder = StreamingRecognizeRequest.newBuilder()
                .setStreamingConfig(StreamingRecognitionConfig.newBuilder()
                    .setConfig(RecognitionConfig.newBuilder()
                        .setEncoding(RecognitionConfig.AudioEncoding.LINEAR16)
                        .setSampleRateHertz(16000)
                        .setLanguageCode("en-US"))
                    .setInterimResults(true));
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
    @Override
    public void handleBinaryMessage(WebSocketSession session, BinaryMessage message) {
        try {
            StreamingRecognizeRequest request = requestBuilder
                .setAudioContent(message.getPayload().asReadOnlyBuffer()).build();
            speechClient.streamingRecognizeCallable().call(request).forEach(response -> {
                for (StreamingRecognitionResult result : response.getResultsList()) {
                    for (SpeechRecognitionAlternative alternative : result.getAlternativesList()) {
                        try {
                            session.sendMessage(new TextMessage(alternative.getTranscript()));
                        } catch (IOException e) {
                            e.printStackTrace();
                        }
                    }
                }
            });
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

实现实时音频流的识别与处理

为处理音频流，我们可以利用Google Cloud的Speech-to-Text API。以下是一个示例：

完整的Spring Boot应用程序

1. Maven依赖

确保在pom.xml文件中添加了Spring Boot、WebSocket以及Google Cloud Speech-to-Text的依赖：

<dependencies>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-websocket</artifactId>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-web</artifactId>
    </dependency>
    <dependency>
        <groupId>com.google.cloud</groupId>
        <artifactId>google-cloud-speech</artifactId>
        <version>1.22.8</version>
    </dependency>
</dependencies>

2. WebSocket配置类

创建WebSocket配置类，注册WebSocket处理器：

import org.springframework.context.annotation.Configuration;
import org.springframework.web.socket.config.annotation.EnableWebSocket;
import org.springframework.web.socket.config.annotation.WebSocketConfigurer;
import org.springframework.web.socket.config.annotation.WebSocketHandlerRegistry;
@Configuration
@EnableWebSocket
public class WebSocketConfig implements WebSocketConfigurer {
    private final AudioWebSocketHandler audioWebSocketHandler;
    public WebSocketConfig(AudioWebSocketHandler audioWebSocketHandler) {
        this.audioWebSocketHandler = audioWebSocketHandler;
    }
    @Override
    public void registerWebSocketHandlers(WebSocketHandlerRegistry registry) {
        registry.addHandler(audioWebSocketHandler, "/audio").setAllowedOrigins("*");
    }
}

3. 实现WebSocket处理器

在WebSocket处理器中，处理来自客户端的音频数据流，并调用Google Cloud Speech-to-Text API进行识别。我们将语言代码设置为中文（简体）。

import org.springframework.web.socket.BinaryMessage;
import org.springframework.web.socket.TextMessage;
import org.springframework.web.socket.WebSocketSession;
import org.springframework.web.socket.handler.BinaryWebSocketHandler;
import org.springframework.stereotype.Component;
import com.google.cloud.speech.v1.*;
import com.google.protobuf.ByteString;
import java.io.IOException;
import java.util.concurrent.*;
@Component
public class AudioWebSocketHandler extends BinaryWebSocketHandler {
    private final ExecutorService executorService = Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors());
    private SpeechClient speechClient;
    private StreamingRecognizeRequest.Builder requestBuilder;
    public AudioWebSocketHandler() {
        try {
            speechClient = SpeechClient.create();
            StreamingRecognitionConfig config = StreamingRecognitionConfig.newBuilder()
                .setConfig(RecognitionConfig.newBuilder()
                    .setEncoding(RecognitionConfig.AudioEncoding.LINEAR16)
                    .setSampleRateHertz(16000)
                    .setLanguageCode("zh-CN")) // 设置语言代码为中文
                .setInterimResults(true)
                .build();
            requestBuilder = StreamingRecognizeRequest.newBuilder()
                .setStreamingConfig(config);
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
    @Override
    public void handleBinaryMessage(WebSocketSession session, BinaryMessage message) {
        executorService.submit(() -> processAudio(session, message));
    }
    private void processAudio(WebSocketSession session, BinaryMessage message) {
        try {
            ByteString audioBytes = ByteString.copyFrom(message.getPayload().array());
            StreamingRecognizeRequest request = requestBuilder.setAudioContent(audioBytes).build();
            speechClient.streamingRecognizeCallable().call(request).forEach(response -> handleResponse(session, response));
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
    private void handleResponse(WebSocketSession session, StreamingRecognizeResponse response) {
        response.getResultsList().forEach(result -> result.getAlternativesList().forEach(alternative -> {
            try {
                session.sendMessage(new TextMessage(alternative.getTranscript()));
            } catch (IOException e) {
                e.printStackTrace();
            }
        }));
    }
}

4. 启动类

最后，实现Spring Boot的主启动类：

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class SpeechRecognitionApplication {
    public static void main(String[] args) {
        SpringApplication.run(SpeechRecognitionApplication.class, args);
    }
}

客户端实现

确保客户端能够通过WebSocket连接到服务器，并发送音频数据。这里提供一个HTML5和JavaScript的示例：

<!DOCTYPE html>
<html>
<head>
    <title>WebSocket Audio Stream</title>
</head>
<body>
    <h2>实时语音识别</h2>
    <button id="start">开始录音</button>
    <button id="stop">停止录音</button>
    <script>
        let audioContext, mediaRecorder, socket;
        let bufferSize = 2048;
        let pcmData = [];
        document.getElementById('start').onclick = async () => {
            audioContext = new (window.AudioContext || window.webkitAudioContext)();
            let stream = await navigator.mediaDevices.getUserMedia({ audio: true });
            let input = audioContext.createMediaStreamSource(stream);
            let processor = audioContext.createScriptProcessor(bufferSize, 1, 1);
            processor.onaudioprocess = (event) => {
                let audioData = event.inputBuffer.getChannelData(0);
                let data = convertFloat32ToInt16(audioData);
                pcmData.push(...data);
                
                if (pcmData.length >= bufferSize) {
                    if (socket && socket.readyState === WebSocket.OPEN) {
                        socket.send(new Int16Array(pcmData).buffer);
                        pcmData = [];
                    }
                }
            };
            input.connect(processor);
            processor.connect(audioContext.destination);
            socket = new WebSocket('ws://localhost:8080/audio');
        };
        document.getElementById('stop').onclick = () => {
            audioContext.close();
            socket.close();
        };
        function convertFloat32ToInt16(buffer) {
            let l = buffer.length;
            let buf = new Int16Array(l);
            while (l--) {
                buf[l] = buffer[l] * 0x7FFF; // Convert float to int
            }
            return buf;
        }
    </script>
</body>
</html>