1、离线命令词识别调用主函数

package com.iflytek;
import com.iflytek.util.Step2_asr_thread;
import com.iflytek.util.Step3_audioFormat;
import java.util.Scanner;
import javax.sound.sampled.AudioFormat;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.DataLine;
import javax.sound.sampled.TargetDataLine;

/**
 * 请注意！！！
 * 1.首先到控制台https://console.xfyun.cn/services/mlcsb下载离线命令词识别的Windows MSC。
 * 2.下载的离线命令词识别Windows MSC解压后,把bin目录下msc文件夹、dll文件、call.bnf文件拷贝到res目录下。
 * 3.最后请替换Step2_ars_thread中的appid值,appid值在下载页面控制台可以看到。
 */

public class OfflineAsrMain {
	//录音相关参数
	public static AudioFormat audioFormat;
	public static TargetDataLine targetDataLine;
	public static void main(String[] args) throws Exception {
		System.out.println("y开始体验离线命令词识别,n结束离线命令词识别");
		Scanner input = new Scanner(System.in);
		String inputContent = input.next();
		long startTime = System.currentTimeMillis();
		if(inputContent.equals("y")){
			audioFormat = Step3_audioFormat.getAudioFormat(audioFormat);//构造具有线性 PCM 编码和给定参数的 AudioFormat。
			DataLine.Info dataLineInfo = new DataLine.Info(TargetDataLine.class, audioFormat);
			targetDataLine = (TargetDataLine) AudioSystem.getLine(dataLineInfo);
			Step2_asr_thread myThread=new Step2_asr_thread();
			myThread.start();
			Scanner input_2 = new Scanner(System.in);
			String inputContent_2 = input_2.next();
			if(inputContent_2.equals("n")){
				targetDataLine.stop();
				targetDataLine.close();
			}
			System.out.println("离线命令词识别操作持续："+(System.currentTimeMillis()-startTime)/1000+"秒！");
			System.exit(0);
		}
	}
}

 2、根据MSC文档用JAVA重写方法

package com.iflytek.service;
import com.iflytek.util.Step1_grammar_callback;
import com.iflytek.util.Step1_lexicon_callback;
import com.sun.jna.Library;
import com.sun.jna.Native;
import com.sun.jna.ptr.IntByReference;

public interface Step1_asr_dll extends Library {
    /**
     * 重点：
     * 1.char *   对应  String
     * 2.int *    对应  IntByReference
     * 3.void *   对应  byte[]，回调函数里此类型也可以用String来对应。
     * 4.int      对应  int
     * 5.无参     对应  void
     * 6.回调函数  对应  根据文档自定义回调函数，实现接口Callback
     */
    //加载dll动态库并实例化,从而使用其内部的方法
    Step1_asr_dll INSTANCE = (Step1_asr_dll) Native.loadLibrary
                             ("res/msc_x64.dll", Step1_asr_dll.class);

    //定义登录方法
    public int MSPLogin(String usr, String pwd, String params);

    //开始一次语音识别。
    public String QISRSessionBegin(String grammarList,String params,IntByReference errorCode);

    //写入本次识别的音频
    public int QISRAudioWrite(String sessionID, byte[] byteArrayAudioData,int waveLen,int audioStatus, IntByReference epStatus,IntByReference recogStatus);

    //获取识别结果。
    public String QISRGetResult(String sessionID,IntByReference rsltStatus,int waitTime, IntByReference errorCode);

    //结束本次语音识别。
    public int QISRSessionEnd(String sessionID,String hints);

    //获取当次语音识别信息，如上行流量、下行流量等
    public int QISRGetParam(String sessionID,String paramName,String paramValue, IntByReference valueLen);

    //构建语法，生成语法ID。有回调
    public int QISRBuildGrammar(String grammarType, String grammarContent, int grammarLength, String params, Step1_grammar_callback grammarCallBack, byte[] userData);

    //更新本地语法词典。有回调
    public int QISRUpdateLexicon(String lexiconName, String lexiconContent, int lexiconLength, String params, Step1_lexicon_callback lexiconCallback, byte[] userData);

    //定义退出方法
    public int MSPLogout();
}

3、 构建语法回调函数

package com.iflytek.util;
import com.sun.jna.Callback;

public class Step1_grammar_callback implements Callback {
    //根据文档写回调方法
    public int build_grm_cb(int errorCode,String info, String userData) {
        System.out.println("构建语法返回的ID信息...:"+info+"错误码"+errorCode+"\n");
        return 0;
    }
}

4、更新词典回调函数

package com.iflytek.util;
import com.sun.jna.Callback;

public class Step1_lexicon_callback implements Callback {
    //根据文档写回调方法
    public int LexiconCallBack(int errorCode, String info, String userData) {
        System.out.println("更新词典返回的信息...:"+info+"错误码:"+errorCode+"\n");
        return 0;
    }
}

5、把调用步骤依次写进线程类

package com.iflytek.util;
import com.iflytek.OfflineAsrMain;
import com.iflytek.service.Step1_asr_dll;
import com.sun.jna.ptr.IntByReference;
import javax.sound.sampled.AudioInputStream;
import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.InputStreamReader;

public class Step2_asr_thread extends Thread{
	public void run() {
		while (true) {
			//登录参数
			String login_config = "appid = 替换你的appid, work_dir = ./res";
			//第一个参数为用户名，第二个参数为密码，传null即可
			int ret = Step1_asr_dll.INSTANCE.MSPLogin(null, null, login_config);
			if (ret != 0) {//登录成功标志ret为0
				System.out.println("登录失败...请检查"+ret);
				System.exit(1);
			} else {
				//System.out.println("请注意，离线命令词call.bnf可以根据语法自定义...");
			}

			//读取call.bnf的内容
			FileInputStream fileInputStream = null;
			String grammarContent = "";
			try {
				fileInputStream = new FileInputStream("./res/call.bnf");
				InputStreamReader inputStreamReader = new InputStreamReader(fileInputStream, "UTF-8");
				BufferedReader bufferedReader = new BufferedReader(inputStreamReader);
				String temp = "";
				while ((temp = bufferedReader.readLine()) != null) {
					grammarContent = grammarContent + temp + "\n";
				}
			} catch (Exception e) {
				e.printStackTrace();
			}
			//System.out.println("语法内容:\n" + grammarContent);

			//构建语法
			Step1_grammar_callback step2_grammar_callback = new Step1_grammar_callback();
			String params = "engine_type = local,asr_res_path = fo|res/asr/common.jet,sample_rate = 16000,grm_build_path = res/asr/GrmBuilld_x64";
			ret = Step1_asr_dll.INSTANCE.QISRBuildGrammar("bnf", grammarContent, grammarContent.getBytes().length, params, step2_grammar_callback, null);
			if (ret == 0) {
				//System.out.println("构建语法成功...");
			} else {
				System.out.println("构建语法失败:" + ret);
			}

			//更新本地语法词典
			/*String lexiconName = "enter";
			String lex_content = "登录软件";
			String lexParams = "engine_type=local,asr_res_path = fo|res/asr/common.jet, sample_rate = 16000,grm_build_path =res/asr/GrmBuilld_x64, grammar_list =call";
			Step3_lexicon_callback step3_lexicon_callback = new Step3_lexicon_callback();
			ret = Step1_asr_dll.INSTANCE.QISRUpdateLexicon(lexiconName, lex_content, lex_content.getBytes().length, lexParams, step3_lexicon_callback, null);
			if (ret == 0) {
				//System.out.println("更新本地语法词典成功...");
			} else {
				System.out.println("更新本地语法词典失败:" + ret);
			}*/

			//开始一次语音识别
			IntByReference errorCode = new IntByReference(-100);
			params = "vad_bos =4000 ,vad_eos = 10000,engine_type = local,asr_res_path = fo|res/asr/common.jet, sample_rate = 16000,grm_build_path = res/asr/GrmBuilld_x64, local_grammar = call,result_type = json, result_encoding = UTF8";
			String session_id = Step1_asr_dll.INSTANCE.QISRSessionBegin(null, params, errorCode);
			if (errorCode.getValue() == 0) {//只有返回0为函数调用成功
				System.out.println("本次会话开启成功...,会话id为:" + session_id);
			} else {
				System.out.println("本次会话开启失败:" + errorCode.getValue());
			}

			//写入识别的音频
			try {
				//给构建语法、更新本地语法词典点时间
				Thread.sleep(100);
				System.err.println("\033[43;34;4m" + "请开始说出命令..." + "\033[0m");
				//间隔400ms给用户反映时间
				Thread.sleep(500);
			} catch (Exception e) {
				e.printStackTrace();
			}
			IntByReference epStatus = new IntByReference(-100);
			IntByReference recogStatus = new IntByReference(-100);
			//16k采样率的16位音频，一帧的大小为640Byte(来自Windows SDK的说明)
			int frameSize = 640;
			//用来告知MSC音频发送是否完成
			int audioStatus = 1;
			//反复调用QISRAudioWrite写音频方法，直到音频写完为止
			//long startTime=System.currentTimeMillis();
			try {
				final byte[] audioDataByteArray = new byte[frameSize];
				while (true) {
					OfflineAsrMain.targetDataLine.open(OfflineAsrMain.audioFormat);
					OfflineAsrMain.targetDataLine.start();
					int len = new AudioInputStream(OfflineAsrMain.targetDataLine).read(audioDataByteArray);
					//long endTime=System.currentTimeMillis();//||endTime-startTime>60000
					if (len == -1 || epStatus.getValue() == 3) {//调用麦克风时候,len == -1将不会被执行...
						//||(endTime-startTime>60*1000)
						audioStatus = 4;//最后帧
						ret = Step1_asr_dll.INSTANCE.QISRAudioWrite(session_id, audioDataByteArray, len, audioStatus, epStatus, recogStatus);
						if (ret == 0) {
							//System.out.println("最后一帧音频写入正常");
						} else {
							System.out.println("最后一帧音频写入异常:" + ret);
						}
						Thread.sleep(1500);
						break;  //文件读完，跳出循环
					} else {
						//反复调用
						ret = Step1_asr_dll.INSTANCE.QISRAudioWrite(session_id, audioDataByteArray, len, audioStatus, epStatus, recogStatus);
					}
					audioStatus = 2;//中间帧
					if (ret == 0) {
						//System.out.println("音频写入正常");
					} else {
						System.out.println("音频写入异常:" + ret);
					}
					// 如果是实时采集音频，可以省略此操作。5KB 大小的16KPCM 持续的时间是160 毫秒
					//Thread.sleep(160);
				}
			} catch (Exception e) {
				e.printStackTrace();
			}

			//获取识别结果
			IntByReference rsltStatus = new IntByReference(-100);
			String grammarResult = Step1_asr_dll.INSTANCE.QISRGetResult(session_id, rsltStatus, 0, errorCode);
			if(grammarResult!=null){
				System.out.println("命令词识别结果:" + grammarResult);
			}

			//终止会话
			ret = Step1_asr_dll.INSTANCE.QISRSessionEnd(session_id, "正常终止");
			if (ret == 0) {
				//System.out.println("本次会话正常终止...");
			} else {
				System.out.println("本次会话异常终止...");
			}

			//执行退出
			ret = Step1_asr_dll.INSTANCE.MSPLogout();
			if (ret == 0) {
				//System.out.println("正常退出...");
			} else {
				System.out.println("异常退出...");
			}
		}
	}
}

6、录音生成16K、16BIT单声道的音频流

package com.iflytek.util;
import javax.sound.sampled.AudioFormat;

public class Step3_audioFormat {
    //构造线程参数
    //16k采样率的16bit音频，一帧的大小为640B, 时长20ms
    /**
     sampleRate - 每秒样品数
     sampleSizeInBits - 每个样本中的位数
     channels - 通道数（1为mono，2为立体声等）
     signed - 表示数据是签名还是无符号
     bigEndian - 指示单个样本的数据是否以大字节顺序存储（ false表示小端）
     */
    public static AudioFormat getAudioFormat(AudioFormat audioFormat) {
        audioFormat=new AudioFormat(16000F, 16,
                                   1,true,false);
        // true,false 指示是以 big-endian 顺序还是以 little-endian 顺序存储音频数据。
        return audioFormat;//构造具有线性 PCM 编码和给定参数的 AudioFormat。
    }
}

7、放置讯飞开放平台下载Linux/Windows中所带的资源

8、Linux代码基本类似，注意加载SO库就行和放置资源

package com.iflytek.service;
import com.iflytek.OfflineAsrMain;
import com.iflytek.util.Step1_grammar_callback;
import com.iflytek.util.Step1_lexicon_callback;
import com.sun.jna.Library;
import com.sun.jna.Native;
import com.sun.jna.ptr.IntByReference;

public interface Step1_asr_so extends Library {
    /**
     * 重点：
     * 1.char *   对应  String
     * 2.int *    对应  IntByReference
     * 3.void *   对应  byte[]，回调函数里此类型需用String来对应。
     * 4.int      对应  int
     * 5.无参     对应  void
     * 6.回调函数  对应  根据文档自定义回调函数，实现接口Callback
     */
    //加载so动态库并实例化,从而使用其内部的方法
    Step1_asr_so INSTANCE = (Step1_asr_so) Native.loadLibrary
            (OfflineAsrMain.userPath+"res/libmsc.so", Step1_asr_so.class);

    //定义登录方法
    public int MSPLogin(String usr, String pwd, String params);

    //开始一次语音识别。
    public String QISRSessionBegin(String grammarList,String params,IntByReference errorCode);

    //写入本次识别的音频
    public int QISRAudioWrite(String sessionID, byte[] byteArrayAudioData,int waveLen,int audioStatus, IntByReference epStatus,IntByReference recogStatus);

    //获取识别结果。
    public String QISRGetResult(String sessionID,IntByReference rsltStatus,int waitTime, IntByReference errorCode);

    //结束本次语音识别。
    public int QISRSessionEnd(String sessionID,String hints);

    //获取当次语音识别信息，如上行流量、下行流量等
    public int QISRGetParam(String sessionID,String paramName,String paramValue, IntByReference valueLen);

    //构建语法，生成语法ID。有回调
    public int QISRBuildGrammar(String grammarType, String grammarContent, int grammarLength, String params, Step1_grammar_callback grammarCallBack, byte[] userData);

    //更新本地语法词典。有回调
    public int QISRUpdateLexicon(String lexiconName, String lexiconContent, int lexiconLength, String params, Step1_lexicon_callback lexiconCallback, byte[] userData);

    //定义退出方法
    public int MSPLogout();
}