Java 离线中文语音文字识别功能的实现代码
目录
1、pom文件如下：
2、工程结构：
3、语音识别工具类
4、前端交互
5、前端页面
6、运行效果
项目需要，要实现类似小爱同学的语音控制功能，并且要离线，不能花公司一分钱。第一步就是需要把音频文字化。经过各种资料搜集后，选择了vosk。这是vosk的官方介绍：
Vosk is a speech recognition toolkit. The best things in Vosk are:
Supports 19+ languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh. More to come.
Works offline, even on lightweight devices - Raspberry Pi, Android, iOS
Installs with simple pip3 install vosk
Portable per-language models are only 50Mb each, but there are much bigger server models available.
Provides streaming API for the best user experience (unlike popular speech-recognition python packages)
There are bindings for different programming languages, too - java/csharp/javascript etc.
Allows quick reconfiguration of vocabulary for best accuracy.
Supports speaker identification beside simple speech recognition.
选择它的理由，开源、可离线、可使用第三方的训练模型，本次使用的官方提供的中文训练模型，如果有需要可自行训练，不过成本太大。具体见官网：https://alphacephei.com/vosk/，官方demo：https://github.com/alphacep/vosk-api。
本次使用springboot +maven实现，官方demo为springboot+gradle。
1、pom文件如下：<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.5.4</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<groupId>com.example</groupId>
<artifactId>voice</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>voice-ai</name>
<description>Demo project for Spring Boot</description>
<properties>
<java.version>1.8</java.version>
</properties>
<repositories>
<repository>
<id>com.alphacephei</id>
<name>vosk</name>
<url>https://alphacephei.com/maven/</url>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>net.java.dev.jna</groupId>
<artifactId>jna</artifactId>
<version>5.7.0</version>
</dependency>
<dependency>
<groupId>com.alphacephei</groupId>
<artifactId>vosk</artifactId>
<version>0.3.30</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.8</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
特别说明一下，vosk的包在常见的maven仓库里面是没有的，所以需要指定下载地址。
2、工程结构：
public class VoiceUtil {
@Value("${leenleda.vosk.model}")
private String VOSKMODELPATH;
public String getWord(String filePath) throws IOException, UnsupportedAudioFileException {
Assert.isTrue(StringUtils.hasLength(VOSKMODELPATH), "无效的VOS模块！");
byte[] bytes = Files.readAllBytes(Paths.get(filePath));
// 转换为16KHZ
reSamplingAndSave(bytes, filePath);
File f = new File(filePath);
RandomAccessFile rdf = null;
rdf = new RandomAccessFile(f, "r");
log.info("声音尺寸:{}", toInt(read(rdf, 4, 4)));
log.info("音频格式:{}", toShort(read(rdf, 20, 2)));
short track=toShort(read(rdf, 22, 2));
log.info("1 单声道 2 双声道: {}", track);
log.info("采样率、音频采样级别 16000 = 16KHz: {}", toInt(read(rdf, 24, 4)));
log.info("每秒波形的数据量：{}", toShort(read(rdf, 22, 2)));
log.info("采样帧的大小：{}", toShort(read(rdf, 32, 2)));
log.info("采样位数：{}", toShort(read(rdf, 34, 2)));
rdf.close();
LibVosk.setLogLevel(LogLevel.WARNINGS);
try (Model model = new Model(VOSKMODELPATH);
InputStream ais = AudioSystem.getAudioInputStream(new BufferedInputStream(new FileInputStream(filePath)));
// 采样率为音频采样率的声道倍数
Recognizer recognizer = new Recognizer(model, 16000*track)) {
int nbytes;
byte[] b = new byte[4096];
int i = 0;
while ((nbytes = ais.read(b)) >= 0) {
i += 1;
if (recognizer.acceptWaveForm(b, nbytes)) {
// System.out.println(recognizer.getResult());
} else {
// System.out.println(recognizer.getPartialResult());
}
}
String result = recognizer.getFinalResult();
log.info("识别结果：{}", result);
if (StringUtils.hasLength(result)) {
JSONObject jsonObject = JSON.parseObject(result);
return jsonObject.getString("text").replace(" ", "");
}
return "";
}
}
public static int toInt(byte[] b) {
return (((b[3] & 0xff) << 24) + ((b[2] & 0xff) << 16) + ((b[1] & 0xff) << 8) + ((b[0] & 0xff) << 0));
}
public static short toShort(byte[] b) {
return (short) ((b[1] << 8) + (b[0] << 0));
}
public static byte[] read(RandomAccessFile rdf, int pos, int length) throws IOException {
rdf.seek(pos);
byte result[] = new byte[length];
for (int i = 0; i < length; i++) {
result[i] = rdf.readByte();
}
return result;
}
public static void reSamplingAndSave(byte[] data, String path) throws IOException, UnsupportedAudioFileException {
WaveFileReader reader = new WaveFileReader();
AudioInputStream audioIn = reader.getAudioInputStream(new ByteArrayInputStream(data));
AudioFormat srcFormat = audioIn.getFormat();
int targetSampleRate = 16000;
AudioFormat dstFormat = new AudioFormat(srcFormat.getEncoding(),
targetSampleRate,
srcFormat.getSampleSizeInBits(),
srcFormat.getChannels(),
srcFormat.getFrameSize(),
srcFormat.getFrameRate(),
srcFormat.isBigEndian());
AudioInputStream convertedIn = AudioSystem.getAudioInputStream(dstFormat, audioIn);
File file = new File(path);
WaveFileWriter writer = new WaveFileWriter();
writer.write(convertedIn, AudioFileFormat.Type.WAVE, file);
}
}
有几点需要说明一下，官方demo里面对采集率是写死了的，为16000。这是以16KHz来算的，所以我把所有拿到的音频都转成了16KHz。还有采集率的设置，需要设置为声道数的倍数。
4、前端交互@RestController
public class VoiceAiController {
@Autowired
VoiceUtil voiceUtil;
@PostMapping("/getWord")
public String getWord(MultipartFile file) {
String path = "G:\\leenleda\\application\\voice-ai\\" + new Date().getTime() + ".wav";
File localFile = new File(path);
try {
file.transferTo(localFile); //把上传的文件保存至本地
System.out.println(file.getOriginalFilename() + " 上传成功");
// 上传成功，开始解析
String text = voiceUtil.getWord(path);
localFile.delete();
return text;
} catch (IOException | UnsupportedAudioFileException e) {
e.printStackTrace();
localFile.delete();
return "上传失败";
}
}
}
5、前端页面
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>声音转换</title>
</head>
<body>
<div>
<audio controls autoplay></audio>
<input id="start" type="button" value="录音" />
<input id="stop" type="button" value="停止" />
<input id="play" type="button" value="播放" />
<input id="upload" type="button" value="提交" />
<div id="text">
</div>
</div>
<script src="http://libs.baidu.com/jquery/2.1.4/jquery.min.js"></script>
<script type="text/javascript" src="HZRecorder.js"></script>
<script>
var recorder;
var audio = document.querySelector('audio');
$("#start").click(function () {
HZRecorder.get(function (rec) {
recorder = rec;
recorder.start();
});
})
$("#stop").click(function () {
recorder.stop();
})
$("#play").click(function () {
recorder.play(audio);
})
$("#upload").click(function () {
recorder.upload("/admin/getWord", function (state, e) {
switch (state) {
case 'uploading':
//var percentComplete = Math.round(e.loaded * 100 / e.total) + '%';
break;
case 'ok':
//alert(e.target.responseText);
// alert("上传成功");
break;
case 'error':
alert("上传失败");
break;
case 'cancel':
alert("上传被取消");
break;
}
});
})
</script>
</body>
</html>
(function (window) {
//兼容
window.URL = window.URL || window.webkitURL;
navigator.getUserMedia = navigator.getUserMedia || navigator.webkitGetUserMedia || navigator.mozGetUserMedia || navigator.msGetUserMedia;
var HZRecorder = function (stream, config) {
config = config || {};
config.sampleBits = 16; //采样数位 8, 16
config.sampleRate = 16000; //采样率(1/6 44100)
var context = new AudioContext();
var audioInput = context.createMediaStreamSource(stream);
var recorder = context.createScriptProcessor(4096, 1, 1);
var audioData = {
size: 0 //录音文件长度
, buffer: [] //录音缓存
, inputSampleRate: context.sampleRate //输入采样率
, inputSampleBits: 16 //输入采样数位 8, 16
, outputSampleRate: config.sampleRate //输出采样率
, oututSampleBits: config.sampleBits //输出采样数位 8, 16
, input: function (data) {
this.buffer.push(new Float32Array(data));
this.size += data.length;
}
, compress: function () { //合并压缩
//合并
var data = new Float32Array(this.size);
var offset = 0;
for (var i = 0; i < this.buffer.length; i++) {
data.set(this.buffer[i], offset);
offset += this.buffer[i].length;
}
//压缩
var compression = parseInt(this.inputSampleRate / this.outputSampleRate);
var length = data.length / compression;
var result = new Float32Array(length);
var index = 0, j = 0;
while (index < length) {
result[index] = data[j];
j += compression;
index++;
}
return result;
}
, encodeWAV: function () {
var sampleRate = Math.min(this.inputSampleRate, this.outputSampleRate);
var sampleBits = Math.min(this.inputSampleBits, this.oututSampleBits);
var bytes = this.compress();
var dataLength = bytes.length * (sampleBits / 8);
var buffer = new ArrayBuffer(44 + dataLength);
var data = new DataView(buffer);
var channelCount = 1;//单声道
var offset = 0;
var writeString = function (str) {
for (var i = 0; i < str.length; i++) {
data.setUint8(offset + i, str.charCodeAt(i));
}
}
// 资源交换文件标识符
writeString('RIFF'); offset += 4;
// 下个地址开始到文件尾总字节数,即文件大小-8
data.setUint32(offset, 36 + dataLength, true); offset += 4;
// WAV文件标志
writeString('WAVE'); offset += 4;
// 波形格式标志
writeString('fmt '); offset += 4;
// 过滤字节,一般为 0x10 = 16
data.setUint32(offset, 16, true); offset += 4;
// 格式类别 (PCM形式采样数据)
data.setUint16(offset, 1, true); offset += 2;
// 通道数
data.setUint16(offset, channelCount, true); offset += 2;
// 采样率,每秒样本数,表示每个通道的播放速度
data.setUint32(offset, sampleRate, true); offset += 4;
// 波形数据传输率 (每秒平均字节数) 单声道×每秒数据位数×每样本数据位/8
data.setUint32(offset, channelCount * sampleRate * (sampleBits / 8), true); offset += 4;
// 快数据调整数 采样一次占用字节数 单声道×每样本的数据位数/8
data.setUint16(offset, channelCount * (sampleBits / 8), true); offset += 2;
// 每样本数据位数
data.setUint16(offset, sampleBits, true); offset += 2;
// 数据标识符
writeString('data'); offset += 4;
// 采样数据总数,即数据总大小-44
data.setUint32(offset, dataLength, true); offset += 4;
// 写入采样数据
if (sampleBits === 8) {
for (var i = 0; i < bytes.length; i++, offset++) {
var s = Math.max(-1, Math.min(1, bytes[i]));
var val = s < 0 ? s * 0x8000 : s * 0x7FFF;
val = parseInt(255 / (65535 / (val + 32768)));
data.setInt8(offset, val, true);
}
} else {
for (var i = 0; i < bytes.length; i++, offset += 2) {
var s = Math.max(-1, Math.min(1, bytes[i]));
data.setInt16(offset, s < 0 ? s * 0x8000 : s * 0x7FFF, true);
}
}
return new Blob([data], { type: 'audio/wav' });
}
};
//开始录音
this.start = function () {
audioInput.connect(recorder);
recorder.connect(context.destination);
}
//停止
this.stop = function () {
recorder.disconnect();
}
//获取音频文件
this.getBlob = function () {
this.stop();
return audioData.encodeWAV();
}
//回放
this.play = function (audio) {
audio.src = window.URL.createObjectURL(this.getBlob());
}
//上传
this.upload = function (url, callback) {
var fd = new FormData();
fd.append("file", this.getBlob());
var xhr = new XMLHttpRequest();
if (callback) {
xhr.upload.addEventListener("progress", function (e) {
callback('uploading', e);
}, false);
xhr.addEventListener("load", function (e) {
callback('ok', e);
}, false);
xhr.addEventListener("error", function (e) {
callback('error', e);
}, false);
xhr.addEventListener("abort", function (e) {
callback('cancel', e);
}, false);
}
xhr.open("POST", url);
xhr.send(fd);
xhr.onreadystatechange = function () {
console.log("语音识别结果："+xhr.responseText)
$("#text").append('<h2>'+xhr.responseText+'</h2>');
}
}
//音频采集
recorder.onaudioprocess = function (e) {
audioData.input(e.inputBuffer.getChannelData(0));
//record(e.inputBuffer.getChannelData(0));
}
};
//抛出异常
HZRecorder.throwError = function (message) {
alert(message);
throw new function () { this.toString = function () { return message; } }
}
//是否支持录音
HZRecorder.canRecording = (navigator.getUserMedia != null);
//获取录音机
HZRecorder.get = function (callback, config) {
if (callback) {
if (navigator.getUserMedia) {
navigator.getUserMedia(
{ audio: true } //只启用音频
, function (stream) {
var rec = new HZRecorder(stream, config);
callback(rec);
}
, function (error) {
switch (error.code || error.name) {
case 'PERMISSION_DENIED':
case 'PermissionDeniedError':
HZRecorder.throwError('用户拒绝提供信息。');
break;
case 'NOT_SUPPORTED_ERROR':
case 'NotSupportedError':
HZRecorder.throwError('浏览器不支持硬件设备。');
break;
case 'MANDATORY_UNSATISFIED_ERROR':
case 'MandatoryUnsatisfiedError':
HZRecorder.throwError('无法发现指定的硬件设备。');
break;
default:
HZRecorder.throwError('无法打开麦克风。异常信息:' + (error.code || error.name));
break;
}
});
} else {
HZRecorder.throwErr('当前浏览器不支持录音功能。'); return;
}
}
}
window.HZRecorder = HZRecorder;
})(window);
6、运行效果
到此这篇关于Java 离线中文语音文字识别 的文章就介绍到这了,更多相关java 离线语音文字识别 内容请搜索软件开发网以前的文章或继续浏览下面的相关文章希望大家以后多多支持软件开发网！
