TTS 返回语音优化
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@@ -144,11 +144,6 @@ public class ChatWebSocketHandler {
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log.info("3、开始进行AI回答时间:{}",System.currentTimeMillis()/1000);
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//持续返回数据流给客户端
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try {
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File inputFile = new File(resultPathUrl);
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File outputFile = new File(resultPathUrl);
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// 设置去除尾部的秒数
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float removeSeconds = 0.25f; // 去除最后5秒
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trimEndByTime(inputFile, outputFile, removeSeconds);
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//文件转换成文件流
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ByteBuffer outByteBuffer = convertFileToByteBuffer(resultPathUrl);
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//发送文件流数据
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@@ -410,44 +405,5 @@ public class ChatWebSocketHandler {
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}
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// 裁剪音频文件,去除最后多少秒
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public void trimEndByTime(File inputFile, File outputFile, float removeSeconds) {
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try {
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// 获取音频输入流
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AudioInputStream audioInputStream = AudioSystem.getAudioInputStream(inputFile);
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AudioFormat format = audioInputStream.getFormat();
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// 获取音频文件的总帧数
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long totalFrames = audioInputStream.getFrameLength();
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// 计算音频文件的总时长(秒)
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float totalDuration = totalFrames / format.getSampleRate();
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// 计算新的结束位置(去除指定的时间后)
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long newEndFrame = (long) ((totalDuration - removeSeconds) * format.getSampleRate());
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// 确保裁剪的结束帧在合理范围内
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if (newEndFrame < 0) {
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System.out.println("去除的时间超过了音频的总时长");
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return;
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}
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// 创建一个新的输入流,裁剪音频数据
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AudioInputStream trimmedStream = new AudioInputStream(
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audioInputStream,
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format,
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newEndFrame
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);
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// 创建新的文件并保存裁剪后的音频
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AudioSystem.write(trimmedStream, AudioFileFormat.Type.WAVE, outputFile);
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System.out.println("裁剪后的音频已保存到: " + outputFile.getAbsolutePath());
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audioInputStream.close();
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} catch (Exception e) {
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e.printStackTrace();
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}
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}
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}
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@@ -169,6 +169,7 @@
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<groupId>org.java-websocket</groupId>
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<artifactId>Java-WebSocket</artifactId>
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</dependency>
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<dependency>
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<groupId>org.apache.tomcat.embed</groupId>
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<artifactId>tomcat-embed-websocket</artifactId>
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@@ -1,5 +1,6 @@
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package com.vetti.common.ai.gpt;
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import cn.hutool.core.util.StrUtil;
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import cn.hutool.json.JSONObject;
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import cn.hutool.json.JSONUtil;
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import com.vetti.common.ai.gpt.service.OpenAiStreamListenerService;
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@@ -9,7 +10,9 @@ import org.springframework.stereotype.Component;
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import java.io.IOException;
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import java.util.HashMap;
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import java.util.HashSet;
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import java.util.Map;
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import java.util.Set;
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import java.util.concurrent.TimeUnit;
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/**
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@@ -30,6 +33,12 @@ public class OpenAiStreamClient {
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@Value("${chatGpt.role}")
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private String role;
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// 定义作为分割点的标点符号集合
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private final Set<Character> punctuationSet = new HashSet<>() {{
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add('。'); add('?'); add('!'); add(';'); // 中文标点
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add('.'); add('?'); add('!'); add(';'); // 英文标点
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}};
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/**
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* 发送流式请求
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*
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@@ -42,6 +51,9 @@ public class OpenAiStreamClient {
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.readTimeout(60, TimeUnit.SECONDS)
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.writeTimeout(30, TimeUnit.SECONDS)
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.build();
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// 文本缓冲区
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StringBuffer bufferStr = new StringBuffer();
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// 构建请求参数
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Map<String, Object> requestBody = new HashMap<>();
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requestBody.put("model", model);
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@@ -104,7 +116,19 @@ public class OpenAiStreamClient {
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.getStr("content");
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if (content != null && !content.isEmpty()) {
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listener.onMessage(content);
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if(punctuationSet.contains(content)){
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//说明有标点啦,直接返回
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bufferStr.append(content);
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listener.onMessage(bufferStr.toString());
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}else{
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//加入缓冲区
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if(StrUtil.isEmpty(bufferStr.toString())){
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bufferStr.append(content);
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}else {
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bufferStr.append(" ").append(content);
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}
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}
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}
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} catch (Exception e) {
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listener.onError(new IOException("Parse error: " + e.getMessage()));
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