使用前提与环境准备：服务开通并购买
操作步骤：
1.添加pom依赖
<dependency>
<groupId>com.alibaba.nls</groupId>
<artifactId>nls-sdk-recognizer</artifactId>
<version>2.2.1</version>
</dependency>
2.Code Sample
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import com.alibaba.nls.client.AccessToken;
import com.alibaba.nls.client.protocol.InputFormatEnum;
import com.alibaba.nls.client.protocol.NlsClient;
import com.alibaba.nls.client.protocol.SampleRateEnum;
import com.alibaba.nls.client.protocol.asr.SpeechRecognizer;
import com.alibaba.nls.client.protocol.asr.SpeechRecognizerListener;
import com.alibaba.nls.client.protocol.asr.SpeechRecognizerResponse;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* 此示例演示了：
* ASR一句话识别API调用。
* 动态获取token。
* 通过本地文件模拟实时流发送。
* 识别耗时计算。
*/
//一句话识别 Java SDK 演示
public class SpeechRecognizerDemo {
private static final Logger logger = LoggerFactory.getLogger(SpeechRecognizerDemo.class);
private String appKey;
NlsClient client;
public SpeechRecognizerDemo(String appKey, String id, String secret, String url) {
this.appKey = appKey;
//应用全局创建一个NlsClient实例，默认服务地址为阿里云线上服务地址。
//获取token，实际使用时注意在accessToken.getExpireTime()过期前再次获取。
AccessToken accessToken = new AccessToken(id, secret);
try {
accessToken.apply();
System.out.println("get token: " + accessToken.getToken() + ", expire time: " + accessToken.getExpireTime());
if(url.isEmpty()) {
client = new NlsClient(accessToken.getToken());
}else {
client = new NlsClient(url, accessToken.getToken());
}
} catch (IOException e) {
e.printStackTrace();
}
}
private static SpeechRecognizerListener getRecognizerListener(final int myOrder, final String userParam) {
SpeechRecognizerListener listener = new SpeechRecognizerListener() {
//识别出中间结果。仅当setEnableIntermediateResult为true时，才会返回该消息。
@Override
public void onRecognitionResultChanged(SpeechRecognizerResponse response) {
//getName是获取事件名称，getStatus是获取状态码，getRecognizedText是语音识别文本。
System.out.println("name: " + response.getName() + ", status: " + response.getStatus() + ", result: " + response.getRecognizedText());
}
//识别完毕
@Override
public void onRecognitionCompleted(SpeechRecognizerResponse response) {
//getName是获取事件名称，getStatus是获取状态码，getRecognizedText是语音识别文本。
System.out.println("name: " + response.getName() + ", status: " + response.getStatus() + ", result: " + response.getRecognizedText());
}
@Override
public void onStarted(SpeechRecognizerResponse response) {
System.out.println("myOrder: " + myOrder + "; myParam: " + userParam + "; task_id: " + response.getTaskId());
}
@Override
public void onFail(SpeechRecognizerResponse response) {
//task_id是调用方和服务端通信的唯一标识，当遇到问题时，需要提供此task_id。
System.out.println("task_id: " + response.getTaskId() + ", status: " + response.getStatus() + ", status_text: " + response.getStatusText());
}
};
return listener;
}
//根据二进制数据大小计算对应的同等语音长度
//sampleRate仅支持8000或16000。
public static int getSleepDelta(int dataSize, int sampleRate) {
// 仅支持16位采样。
int sampleBytes = 16;
// 仅支持单通道。
int soundChannel = 1;
return (dataSize * 10 * 8000) / (160 * sampleRate);
}
public void process(String filepath, int sampleRate) {
SpeechRecognizer recognizer = null;
try {
//传递用户自定义参数
String myParam = "user-param";
int myOrder = 1234;
SpeechRecognizerListener listener = getRecognizerListener(myOrder, myParam);
recognizer = new SpeechRecognizer(client, listener);
recognizer.setAppKey(appKey);
//设置音频编码格式。如果是OPUS文件，请设置为InputFormatEnum.OPUS。
recognizer.setFormat(InputFormatEnum.PCM);
//设置音频采样率
if(sampleRate == 16000) {
recognizer.setSampleRate(SampleRateEnum.SAMPLE_RATE_16K);
} else if(sampleRate == 8000) {
recognizer.setSampleRate(SampleRateEnum.SAMPLE_RATE_8K);
}
//设置是否返回中间识别结果
recognizer.setEnableIntermediateResult(true);
//此方法将以上参数设置序列化为JSON发送给服务端，并等待服务端确认。
long now = System.currentTimeMillis();
recognizer.start();
logger.info("ASR start latency : " + (System.currentTimeMillis() - now) + " ms");
File file = new File(filepath);
FileInputStream fis = new FileInputStream(file);
byte[] b = new byte[3200];
int len;
while ((len = fis.read(b)) > 0) {
logger.info("send data pack length: " + len);
recognizer.send(b, len);
//本案例用读取本地文件的形式模拟实时获取语音流，因为读取速度较快，这里需要设置sleep时长。
// 如果实时获取语音则无需设置sleep时长，如果是8k采样率语音第二个参数设置为8000。
int deltaSleep = getSleepDelta(len, sampleRate);
Thread.sleep(deltaSleep);
}
//通知服务端语音数据发送完毕，等待服务端处理完成。
now = System.currentTimeMillis();
//计算实际延迟，调用stop返回之后一般即是识别结果返回时间。
logger.info("ASR wait for complete");
recognizer.stop();
logger.info("ASR stop latency : " + (System.currentTimeMillis() - now) + " ms");
fis.close();
} catch (Exception e) {
System.err.println(e.getMessage());
} finally {
//关闭连接
if (null != recognizer) {
recognizer.close();
}
}
}
public void shutdown() {
client.shutdown();
}
public static void main(String[] args) throws Exception {
String appKey = "XXXXXXXXXX"; //填写appkey
String id = "XXXXXXXXXX"; //填写AccessKey Id
String secret = "XXXXXXXXXX"; //填写AccessKey Secret
String url = "wss://nls-gateway.cn-shanghai.aliyuncs.com/ws/v1"; // 默认值：wss://nls-gateway.cn-shanghai.aliyuncs.com/ws/v1
/* if (args.length == 3) {
appKey = args[0];
id = args[1];
secret = args[2];
} else if (args.length == 4) {
appKey = args[0];
id = args[1];
secret = args[2];
url = args[3];
} else {
System.err.println("run error, need params(url is optional): " + "<app-key> <AccessKeyId> <AccessKeySecret> [url]");
System.exit(-1);
}*/
SpeechRecognizerDemo demo = new SpeechRecognizerDemo(appKey, id, secret, url);
//本案例使用本地文件模拟发送实时流数据。
demo.process("XXXXXXXXX", 16000);
//demo.process("./nls-sample.opus", 16000);
demo.shutdown();
}
}
3.测试结果
myOrder: 1234; myParam: user-param; task_id: 96bdbd62bd4b4df78642c6481fe1dd70
name: RecognitionResultChanged, status: 20000000, result: 北京
name: RecognitionResultChanged, status: 20000000, result: 北京的天气
name: RecognitionCompleted, status: 20000000, result: 北京的天气
更多参考
开发指南
一句话识别
