"feat: 更新ASR服务连接配置,优化录音流处理及模型路径"

This commit is contained in:
2025-06-02 12:38:53 +08:00
parent e638d7907a
commit 232d799575
8 changed files with 242 additions and 26 deletions

178
src/wake/test/stream.ts Normal file
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import vosk from 'vosk';
import { Recording } from '../../recorder/index.ts';
import fs, { WriteStream } from 'fs';
import path from 'path';
import { audioPath, sleep, mySpeechText, MODEL_PATH } from './common.ts';
import { encodeWav, decodeWav } from '../../utils/convert.ts';
const streamText = async (audioFilePath: string) => {
if (!fs.existsSync(MODEL_PATH)) {
console.error('请先下载Vosk模型');
return false;
}
const model = new vosk.Model(MODEL_PATH);
const rec = new vosk.Recognizer({ model: model, sampleRate: 16000 });
const audioBuffer = fs.readFileSync(audioFilePath);
const pcmBuffer = decodeWav(audioBuffer);
for (let i = 0; i < pcmBuffer.length; i += 1024) {
const chunk = pcmBuffer.subarray(i, i + 1024);
if (rec.acceptWaveform(chunk)) {
const result = rec.result();
console.log('Streamed Result:', result);
} else {
const partialResult = rec.partialResult();
console.log('Partial Result:', partialResult);
}
// await sleep(100); // 模拟延时
}
return true;
};
// 测试流式处理
// streamText(mySpeechText)
// .then((result) => {
// console.log('Final Result:', result);
// })
// .catch((error) => {
// console.error('Error during streaming:', error);
// });
const record = async () => {
const recording = new Recording({
sampleRate: 16000,
channels: 1,
});
recording.start();
const stream = recording.stream();
console.log('Recording started...', stream);
const model = new vosk.Model(MODEL_PATH);
const rec = new vosk.Recognizer({
model: model,
sampleRate: 16000,
grammar: ['你', '好', '小', '嗨', '秀'], // 添加唤醒词
});
console.log('Vosk Recognizer initialized...');
// 创建累积缓冲区
let accumulatedBuffer = Buffer.alloc(0);
const PROCESS_SIZE = 4 * 8192; // 合并大约4个8192字节的块 (可根据需要调整)
stream.on('data', (data: Buffer) => {
// const pcmBuffer = decodeWav(data); // 8192 bytes per chunk
const pcmBuffer = data; // 假设数据已经是PCM格式
// 将新数据追加到累积缓冲区
accumulatedBuffer = Buffer.concat([accumulatedBuffer, pcmBuffer]);
// 当积累的数据足够大时处理它
if (accumulatedBuffer.length >= PROCESS_SIZE) {
if (rec.acceptWaveform(accumulatedBuffer)) {
const result = rec.result();
console.log('Recorded Result:', result);
// 检查是否包含唤醒词
if (result.text) {
const detect = detectWakeWord(result.text);
if (detect.detected) {
console.log(`检测到唤醒词: "${detect.word}",置信度: ${detect.confidence}`);
}
// 执行唤醒后的操作
}
} else {
const partialResult = rec.partialResult();
console.log('Partial Result:', partialResult);
}
// 清空累积缓冲区
accumulatedBuffer = Buffer.alloc(0);
}
});
// 添加停止录音的处理
stream.on('end', () => {
// 处理剩余的缓冲区数据
if (accumulatedBuffer.length > 0) {
if (rec.acceptWaveform(accumulatedBuffer)) {
const result = rec.result();
console.log('Final Recorded Result:', result);
}
}
// 获取最终结果
const finalResult = rec.finalResult();
console.log('Final Complete Result:', finalResult);
// 释放资源
rec.free();
model.free();
});
// 返回一个用于停止录音的函数
return {
stop: () => {
recording.stop();
},
};
};
// 添加唤醒配置
const wakeConfig = {
words: ['你好小小', '嗨小小', '小小', '秀秀'],
threshold: 0.75, // 匹配置信度阈值
minWordCount: 2, // 最小词数
};
// 优化唤醒词检测
function detectWakeWord(text: string): { detected: boolean; confidence: number; word: string } {
if (!text || text.length < wakeConfig.minWordCount) return { detected: false, confidence: 0, word: '' };
let bestMatch = { detected: false, confidence: 0, word: '' };
for (const wakeWord of wakeConfig.words) {
// 计算文本与唤醒词的相似度
const confidence = calculateSimilarity(text.toLowerCase(), wakeWord.toLowerCase());
console.log(`检测到唤醒词 "${wakeWord}" 的相似度: ${confidence}`);
if (confidence > wakeConfig.threshold && confidence > bestMatch.confidence) {
bestMatch = { detected: true, confidence, word: wakeWord };
}
}
return bestMatch;
}
// 简单的字符串相似度计算函数
function calculateSimilarity(str1: string, str2: string): number {
if (str1.includes(str2)) return 1.0;
// 计算莱文斯坦距离的简化版本
const longer = str1.length > str2.length ? str1 : str2;
const shorter = str1.length > str2.length ? str2 : str1;
// 如果短字符串为空相似度为0
if (shorter.length === 0) return 0;
// 简单的相似度计算 - 可以替换为更复杂的算法
let matchCount = 0;
for (let i = 0; i <= longer.length - shorter.length; i++) {
const segment = longer.substring(i, i + shorter.length);
let localMatches = 0;
for (let j = 0; j < shorter.length; j++) {
if (segment[j] === shorter[j]) localMatches++;
}
matchCount = Math.max(matchCount, localMatches);
}
return matchCount / shorter.length;
}
// 启动录音并在适当的时候停止
(async () => {
const recorder = await record();
// 可选30秒后自动停止录音
setTimeout(() => {
console.log('Stopping recording...');
recorder.stop();
}, 10 * 30 * 1000);
})();