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语音识别(ASR) 阿里云

时间:2018-05-20 16:39:22      阅读:4058      评论:0      收藏:0      [点我收藏+]

标签:answer   word   nsa   框架   switch   signal   筛选   disabled   lsa   

做语音识别这块的呢,国内领先的有科大讯飞,BAT这几家公司,鉴于使用科大讯飞的接口需要付费,腾讯云的语音识别申请了几天也没给通过,比较了一下阿里和百度的,个人觉得阿里云的好用一些,这篇博客来讲讲怎么讲阿里云的语音识别应用到项目中。

首先是一些链接

阿里云语音识别官网:https://help.aliyun.com/document_detail/30416.html

语音识别demo下载:http://download.taobaocdn.com/freedom/33762/compress/RealtimeDemo.zip?spm=a2c4g.11186623.2.6.5F8mxh&file=RealtimeDemo.zip

语音识别(ASR)使用手册:http://docs-aliyun.cn-hangzhou.oss.aliyun-inc.com/pdf/IntelligentSpeechInteraction-intro_asr-cn-zh-2016-12-23.pdf?spm=a2c4g.11186623.2.3.gMkFE3&file=IntelligentSpeechInteraction-intro_asr-cn-zh-2016-12-23.pdf

 

项目中的应用

  要实现的功能:前端浏览器录取用户说话的录音,然后转换为文字显示在浏览器。例如回答问题后,回答的答案显示在下方

技术分享图片

   流程分析:实现这个功能流程很简单就是浏览器收集到用户的语音输入流后,发送给后台,后台继续将数据发送到阿里云的服务器端,进行语音转文字,完成后将返回的结果进行处理,再返回到前台。

本例中主要分为两个模块,(1)前台获得麦克风的权限进行录音;(2)录制完成将数据发送到后台进行语音转文字的处理。

(1)前台录音

  前台的功能是,点击录音,获取浏览器麦克风权限后,开始录音。点击转换按钮,停止录音,将数据发送到后台进行转换,转换后的结果显示在下方的文本域中,同时出现audio元素标签和文件下载链接,可回放录音和保存文件到本地。
录音相关的js文件来源其他大神,本人将其代码进行部分修改以满足需求。

技术分享图片

JSP页面的代码

<%@ page language="java" contentType="text/html; charset=utf-8" pageEncoding="utf-8"%>  
<% 
   String path = request.getContextPath();
   String basePath = request.getScheme() + "://" + request.getServerName() + ":" + request.getServerPort() + path + "/";
%>
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>Insert title here</title>
</head>
<body>
    <form id="questions">
        <div><h1>回答问题</h1></div>
        <input type="hidden" name="records[0].question" value="AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA">
        <div><h3>问题一:AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA</h3></div>
        <div>
            <button onclick="startRecording(this)" >录音</button>
            <button onclick="uploadAudio(this,1)" disabled>转换</button>
            <div id="recordingslist1"></div>
        </div>
        <textarea id="audioText1" name="records[0].answer" rows="3" cols="50" style="font-size:18px"></textarea>
        
        <input type="hidden" name="records[1].question" value="BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB">
        <div><h3>问题二:BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB</h3></div>
        <div>
            <button onclick="startRecording(this)" >录音</button>
            <button onclick="uploadAudio(this,2)" disabled>转换</button>
            <div id="recordingslist2"></div>
        </div>
        <textarea id="audioText2" name="records[1].answer" rows="3" cols="50" style="font-size:18px"></textarea>
        
        <input type="hidden" name="records[2].question" value="CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC">
        <div><h3>问题三:CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC</h3></div>
        <div>
            <button onclick="startRecording(this)" >录音</button>
            <button onclick="uploadAudio(this,3)" disabled>转换</button>
            <div id="recordingslist3"></div>
        </div>
        <textarea id="audioText3" name="records[2].answer" rows="3" cols="50" style="font-size:18px"></textarea>
        <br>
        <input type="button" onclick="save()"  value="保存录音"/>
    </form>
        <a href="<%=path %>/audio/getAllRecord">查看记录详情</a>
    
    <form action="<%=path %>/audio/getaudio" method="post" enctype="multipart/form-data">
       <h2>文件上传</h2>
                    文件:<input type="file" name="audioData"/><br/><br/>
          <input type="submit" value="上传"/>
    </form>
    
    <script type="text/javascript" src="resources/js/HZRecorder.js"></script>
    <script type="text/javascript" src="resources/js/jquery-1.11.1.js"></script>
    
    <script>
        function save() {
            $.ajax({
                type: "POST",
                dataType: "json",
                url: "<%=path %>/audio/saveRecord",
                data: $(‘#questions‘).serialize(),
                success: function (result) {
                    if (result) {
                        alert("添加成功");
                    }else {
                        alert("添加失败");
                    }
                },
                error : function() {
                    alert("异常!");
                }
            });
        }
    
        var recorder;
        var audio = document.querySelector(‘audio‘);
        
        // 开始录音
        function startRecording(button) {
            button.disabled = true;
                button.nextElementSibling.disabled = false;
            HZRecorder.get(function (rec) {
                recorder = rec;
                recorder.start();
            });
        }
        
        // 播放录音
        function playRecording() {
            recorder.play(audio);
        }
        
        // 转换录音
        function uploadAudio(button,num) {
            button.disabled = true;
                button.previousElementSibling.disabled = false;
            recorder.stop();
            recorder.upload("<%=path %>/audio/getaudio", num);
            
            createDownloadLink(num);
            
        }
        
        // 创建下载链接
        function createDownloadLink(num) {
            var blob = recorder.getBlob();
              var url = URL.createObjectURL(blob);
              var div = document.createElement(‘div‘);
              var au = document.createElement(‘audio‘);
              var hf = document.createElement(‘a‘);
              var record = "recordingslist"+num;
              
              au.controls = true;
              au.src = url;
              hf.href = url;
              hf.download = new Date().toISOString() + ‘.wav‘;
              hf.innerHTML = hf.download;
              div.appendChild(au);
              div.appendChild(hf);
                document.getElementById(record).appendChild(div);
          }
        
    </script>

</body>
</html>

 

引用的js文件 HZRecorder.js

(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 = config.sampleBits || 16;      //采样数位 8, 16
        config.sampleRate = config.sampleRate || (16000);   //采样率(1/6 44100)

        var context = new (window.webkitAudioContext || window.AudioContext)();
        var audioInput = context.createMediaStreamSource(stream);
        var createScript = context.createScriptProcessor || context.createJavaScriptNode;
        var recorder = createScript.apply(context, [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());
        }

        //转换
        this.upload = function (url, num) {
            var id = "audioText"+num;
            var fd = new FormData();
            fd.append("audioData", this.getBlob());
            var xhr = new XMLHttpRequest();
            
            xhr.open("POST", url);
            xhr.send(fd);
            
            xhr.onreadystatechange = function () {
              if (xhr.readyState == 4 && xhr.status == 200) {
                  document.getElementById(id).value += xhr.responseText;
              } 
            };
        }

        //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.name));
                                break;
                        }
                    });
            } else {
                HZRecorder.throwErr(‘当前浏览器不支持录音功能。‘); return;
            }
        }
    }

    window.HZRecorder = HZRecorder;

})(window);

 

 

页面中也没有多少要注意的问题。注意的是每一个问题上方都有一个隐藏域,里面的值是问题的内容,这样做是为了将问题和答案一起存放在数据库中,因为form只能提交input中的内容,所以想出了这个办法,不知道还有没有其他方式。

 

(2)后台转换(SSM框架)

录音文件流以文件上传的方式传到后台(这里不必将文件流转换成音频文件,因为阿里云的实时语音识别Demo中是将文件转化为InputStream,再进行转文字,可直接获得MultipartFile的InputStream传给语音转换)

录音文件时长超过13分钟左右,在转换的过程中,通信会被关闭(即录音20分钟,只会转换10分钟的内容,本人目前不清楚具体的原因)暂时的解决办法是将上传的录音文件分割成两部分,分别执行转换的方法。

RecordController.java

package cn.com.sysystem.controller;

import java.io.ByteArrayInputStream;
import java.io.InputStream;
import java.util.List;

import javax.annotation.Resource;
import javax.servlet.http.HttpServletRequest;

import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.ResponseBody;
import org.springframework.web.multipart.MultipartFile;

import cn.com.sysystem.base.util.RealtimeAsr;
import cn.com.sysystem.entity.RecordEntity;
import cn.com.sysystem.model.RecordModel;
import cn.com.sysystem.service.RecordService;


@Controller
@RequestMapping("/audio")
public class RecordController{
    
    @Resource
    RecordService recordService;

    @ResponseBody
    @RequestMapping(value = "/getaudio" ,produces = "application/json; charset=utf-8")
    public String getaudio(MultipartFile audioData,HttpServletRequest request) throws Exception  {
        StringBuffer sb = new StringBuffer(2000);
        if (audioData != null) {
            
            byte[] bytes = audioData.getBytes();
            // 当录音文件过大时,将文件分割成两段
            if (bytes.length < 20000000) {
                InputStream inputStream = audioData.getInputStream();
                sb.append(getText(inputStream));
            } else {
                byte[] tmp1 = new byte[bytes.length/2];
                byte[] tmp2 = new byte[bytes.length-tmp1.length];
                
                System.arraycopy(bytes, 0, tmp1, 0, tmp1.length);
                System.arraycopy(bytes, tmp1.length, tmp2, 0, tmp2.length);
                
                InputStream input1 = new ByteArrayInputStream(tmp1);
                InputStream input2 = new ByteArrayInputStream(tmp2);
                
                sb.append(getText(input1));
                sb.append(getText(input2));
            }
  
        }else {
            return "文件上传失败";
        }
        return sb.toString();
    }
    
    @ResponseBody
    @RequestMapping(value = "/saveRecord")
    public boolean saveRecord(RecordModel recordlist) throws Exception  {
        boolean flag = true;
        List<RecordEntity> records = recordlist.getRecords();
        for (RecordEntity recordEntity : records) {
            int row = recordService.saveRecord(recordEntity);
            if (row < 0) {
                flag = false;
            }
        }
        return flag;
        
    }
    
    @RequestMapping(value = "/getAllRecord")
    public String getAllRecord(HttpServletRequest request) throws Exception {
        List<RecordEntity> allRecord = recordService.getAllRecord();
        request.setAttribute("recordList", allRecord);
        return "showrecord";
    }
    
    /**
     * 将语音输入流转换为文字
     * @param input
     * @return
     */
    private synchronized String getText(InputStream input) {
        StringBuilder finaltext = new StringBuilder(2000);
        List<String> results = null;
        
        RealtimeAsr realtimeAsr = new RealtimeAsr();
        results = realtimeAsr.AliAudio2Text(input);
        
        // 去除集合中含有status_code = 0的元素
        results.removeIf(p -> p.indexOf("\"status_code\":0") == -1);
        
        for (String str : results) {
            String text = "";
            String[] split = str.split(",");
            text = split[split.length-1];
            text = text.substring(8, text.length()-2);
            finaltext.append(text);
        }
        
        // 清空集合
        results.clear();
        
        return finaltext.toString();
    }

}

 

Controller中getText方法,创建RealtimeAsr类的对象,调用AliAudio2Text方法获得转换结果,RealtimeAsr类如下:

RealtimeAsr.java

package cn.com.sysystem.base.util;

import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.util.ArrayList;
import java.util.List;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONPath;
import com.alibaba.idst.nls.realtime.NlsClient;
import com.alibaba.idst.nls.realtime.NlsFuture;
import com.alibaba.idst.nls.realtime.event.NlsEvent;
import com.alibaba.idst.nls.realtime.event.NlsListener;
import com.alibaba.idst.nls.realtime.protocol.NlsRequest;
import com.alibaba.idst.nls.realtime.protocol.NlsResponse;

/**
 * asr 示例
 * 
 */
public class RealtimeAsr implements NlsListener {
    protected NlsClient client = new NlsClient();
    protected static final String asrSC = "pcm";

    static Logger logger = LoggerFactory.getLogger(RealtimeAsr.class);
    public String filePath = "";
    
    //public String appKey = "nls-service-shurufa16khz";      //社交聊天领域
    public String appKey = "nls-service-multi-domain";          //短视频,视频直播领域,教育,娱乐,文学,法律,财经等
    //public String appKey = "nls-service-en";                    //英语
    
    protected String ak_id = "";              //阿里云的AccessKeyID 和 AccessKeySecret 自行去注册账户,这里就不提供了
    protected String ak_secret = "";
    
    protected String url = "https://nlsapi.aliyun.com/asr/custom/vocabs";
    
    public static List<String> results = new ArrayList<String>(5000);

    public RealtimeAsr() {
    }

    public void shutDown() {
        logger.debug("close NLS client manually!");
        client.close();
        logger.debug("demo done");
    }

    public void start() {
        logger.debug("init Nls client...");
        client.init();
    }

    public void process() {
        logger.debug("open audio file...");
        FileInputStream fis = null;
        try {
            File file = new File(filePath);
            fis = new FileInputStream(file);
        } catch (Exception e) {
            logger.error("fail to open file", e);
        }
        if (fis != null) {
            logger.debug("create NLS future");
            process(fis);
            logger.debug("calling NLS service end");
        }
    }

    public void process(InputStream ins) {
        try {
            NlsRequest req = buildRequest();
            NlsFuture future = client.createNlsFuture(req, this);
            logger.debug("call NLS service");
            byte[] b = new byte[5000];
            int len = 0;
            while ((len = ins.read(b)) > 0) {
                future.sendVoice(b, 0, len);
                //Thread.sleep(200);
            }
            logger.debug("send finish signal!");
            future.sendFinishSignal();

            logger.debug("main thread enter waiting .");
            future.await(100000);

        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    protected NlsRequest buildRequest() {
        NlsRequest req = new NlsRequest();
        req.setAppkey(appKey);
        req.setFormat(asrSC);
        req.setResponseMode("streaming");
        req.setSampleRate(16000);
        
        String body="{\n"
            + "        \"global_weight\": 1,\n"
            + "        \"words\": [\n"
            + "            \"SpringMVC\",\n"
            + "            \"Mybatis\",\n"
            + "            \"Hibernate\"\n"
            + "        ],\n"
            + "        \"word_weights\": {\n"
            + "            \"spring\": 2\n"
            + "        }\n"
            + "    }";
       
        //create
        String result=HttpUtil.sendPost(url,body,ak_id,ak_secret);
        String vocabId=(String)JSONPath.read(result,"vocabulary_id");
        //update
        result=HttpUtil.sendPut(url+"/"+vocabId,body,ak_id,ak_secret);
        req.setVocabularyId(vocabId);
        
        // 设置关键词库ID 使用时请修改为自定义的词库ID
        // req.setKeyWordListId("c1391f1c1f1b4002936893c6d97592f3");
        req.authorize(ak_id, ak_secret);
        return req;

    }

    @Override
    public void onMessageReceived(NlsEvent e) {
        NlsResponse response = e.getResponse();
        response.getFinish();
        if (response.result != null) {
            String tmptext = response.getResult().toString();
            results.add(tmptext);
            //logger.debug("status code = {},get finish is {},get recognize result: {}", response.getStatusCode(),
            //        response.getFinish(), response.getResult());
            if (response.getQuality() != null) {
                logger.info("Sentence {} is over. Get ended sentence recognize result: {}, voice quality is {}",
                        response.result.getSentence_id(), response.getResult(),
                    JSON.toJSONString(response.getQuality()));
            }
        } else {
            logger.info(JSON.toJSONString(response));
        }
    }

    @Override
    public void onOperationFailed(NlsEvent e) {
        logger.error("status code is {}, on operation failed: {}", e.getResponse().getStatusCode(),
                e.getErrorMessage());

    }

    @Override
    public void onChannelClosed(NlsEvent e) {
        logger.debug("on websocket closed.");
    }

    /**
     * @param inputStream
     */
    public List<String> AliAudio2Text(InputStream inputStream)  {
        RealtimeAsr lun = new RealtimeAsr();

        lun.start();
        lun.process(inputStream);
        lun.shutDown();
        
        return results;
    }

}

 

 

注意的地方

1、@RequestMapping(value = "/getaudio" ,produces = "application/json; charset=utf-8")

  produces = "application/json; charset=utf-8" 保证Controller在return中文时乱码的问题。

2、StringBuffer sb = new StringBuffer(2000);

  因为要经常拼接字符串,所以StringBuffer的效率会比String高些,另外还有一个小窍门,就是在new StringBuffer时指定大小,若不指定且内容较长时,会频繁的扩容,影响性能(具体也不知道能提高多少,提高一点是一点吧,同时集合中的list和map也是一样的道理)

3、synchronized

  转换的方法中加入synchronized关键字保证线程安全的目的是,当上一段录音时长较长时,转换需要一定的时间(20分钟的音频,转换过程3分钟左右),若立即开始第二段录音,且时间较短,若不加锁,第二段转换的文本中显示的是第一段的内容。

4、results.removeIf(p -> p.indexOf("\"status_code\":0") == -1);

  这里用到了Java8的Lambda表达式,不明白的同学可以自行了解一下,很好用。

5、

  语音转换收集到的信息如下:(例如说ABCD)
    {"sentence_id":1,"begin_time":280,"current_time":1670,"end_time":-1,"status_code":1,"text":"A"}
    {"sentence_id":1,"begin_time":280,"current_time":1670,"end_time":1793,"status_code":0,"text":"A B C D"}
  其中status_code = 1 表示的是转换的中间状态,status_code = 0表示语音转换完成。所以我们要从集合中筛选出status_code = 0的所有字符串,并截取text的值。

 

语音识别(ASR) 阿里云

标签:answer   word   nsa   框架   switch   signal   筛选   disabled   lsa   

原文地址:https://www.cnblogs.com/ghq120/p/9063287.html

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