第七篇：wed版语音机器人

wed版语音机器人：

　　GitHub项目地址：https://github.com/Yang915/WebToy

　　特别说明：该项目在本机测试，通过浏览器调用系统麦克风（https请求），实际环境在Firefox进行127.0.0.1本机回环测试，其他浏览器不确保正常运行！！！

项目目录说明：

　　

项目主程序：main.py

 1 import os
 2 from flask import Flask, render_template, request
 3 
 4 from BP_get_answer import app_get_answer  # 返回应答语音的蓝图模块
 5 
 6 app = Flask(__name__)
 7 app.debug = True
 8 
 9 app.register_blueprint(app_get_answer)  # 注册蓝图
10 
11 
12 @app.route('/ai_uploader', methods=['GET', 'POST'])
13 def answer():
14     # 接收前端发来的语音消息，并指定路径保存
15     reco_file = request.files.get('reco')
16     # 调用uuid三方模块生成唯一文件名
17     from uuid import uuid4
18     filename = f'{uuid4()}.wav'
19 
20     filepath = os.path.join(os.path.dirname(__file__), 'audio', 'questions', filename)
21     reco_file.save(filepath)
22     # print('语音问题保存路径：',filepath)
23 
24     # 调用语音识别模块，对语音信息进行格式转换保存在指定目录，然后进行识别，得到文字信息
25     from ASR import asr
26     text_question = asr(filepath)
27     # print('语音问题文本',text_question)
28 
29     # 调用自然语言处理模块，对文字信息进行处理，得到回复文字信息
30     from NLP import nlp
31     text_answer = nlp(text_question)
32     # print('语音回答文本',text_answer)
33 
34     # 调用语音合成模块，对回复的文字信息进行合成并保存在指定目录下
35     from TTS import tts
36     answer_filepath = tts(text_answer)
37     print('语音回答文件路径：', answer_filepath)
38 
39     # 获取语音应答消息文件名并返回
40     answer_filename = os.path.basename(answer_filepath)
41     return {'filename': answer_filename}
42 
43 
44 # 返回展示页面
45 @app.route('/record')
46 def get_record():
47     return render_template('WebToy.html')
48 
49 
50 if __name__ == '__main__':
51     app.run()
main.py

模板页面展示：WebToy.html（静态文件从github可以获取）

 1 <!DOCTYPE html>
 2 <html lang="en">
 3 <head>
 4     <meta charset="UTF-8">
 5     <title id="title"></title>
 6 
 7 </head>
 8 <body>
 9 <audio id="player" autoplay controls></audio>
10 <p>
11     <button onclick="start_reco()">开始录音</button>
12 </p>
13 <p>
14     <button onclick="ai_reco()" style="background-color: cornflowerblue">发送语音指令</button>
15 </p>
16 </body>
17 <script type="application/javascript" src="/static/jquery-3.3.1.min.js"></script>
18 <script type="text/javascript" src="/static/Recorder.js"></script>
19 <script type="application/javascript">
20     var serv = "http://127.0.0.1:5000";
21     var audio_context = new AudioContext();//音频内容对象
22     navigator.getUserMedia = (navigator.getUserMedia ||
23         navigator.webkitGetUserMedia ||
24         navigator.mozGetUserMedia ||
25         navigator.msGetUserMedia);
26 
27     navigator.getUserMedia({audio: true}, create_stream, function (err) {
28         console.log(err)
29     });
30 
31     function create_stream(user_media) {
32         var stream_input = audio_context.createMediaStreamSource(user_media);
33         reco = new Recorder(stream_input);
34     }
35 
36 
37     function start_reco() {
38         reco.record();
39     }
40 
41     function ai_reco() {
42         reco.stop();
43 
44         reco.exportWAV(function (wav_file) {
45             console.log(wav_file);
46             var formdata = new FormData(); // form 表单 {key:value}
47             formdata.append("reco", wav_file); // form input type="file"
48             $.ajax({
49                 url: serv + "/ai_uploader",
50                 type: 'post',
51                 processData: false,
52                 contentType: false,
53                 data: formdata,
54                 dataType: 'json',
55                 success: function (data) {
56                     //console.log(data.filename);
57                     var filename = data.filename;
58                     document.getElementById('player').src = serv + '/get_answer/' + filename;
59                 }
60             })
61         });
62 
63         reco.clear();
64     }
65 
66 </script>
67 </html>
WebToy.html

分支--语音识别：ASR.py

 1 import os
 2 from aip import AipSpeech
 3 
 4 APP_ID = '16815394'
 5 API_KEY = 'jM4b8GIG9gzrzySTRq3szK2E'
 6 SECRET_KEY = 'iE626cEpjT1iAVwh24XV5h1QFuR8FPD2'
 7 
 8 client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
 9 
10 
11 # 读取文件
12 def get_file_content(filepath):
13     # 文件格式转换成pcm(前提是需要安装ffmpeg软件并配置环境变量)
14     filename = os.path.basename(filepath)
15     pcm_filename = filename.split('.')[0] + '.pcm'
16     pcm_filepath = os.path.join(os.path.dirname(__file__), 'audio', 'pcm', pcm_filename)
17     cmd_str = f'ffmpeg -y  -i {filepath}  -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {pcm_filepath}'  # ffmpeg软件安装及环境变量配置
18     os.system(cmd_str)  # 调用os.system()在CMD执行命令
19     filepath = pcm_filepath
20 
21     with open(filepath, 'rb') as fp:
22         return fp.read()
23 
24 
25 # 识别本地文件
26 def asr(filePath):
27     pcm_file = get_file_content(filePath)
28     result = client.asr(pcm_file, 'pcm', 16000, {
29         'dev_pid': 1536,
30     })
31     print(result)
32     try:
33         text = result.get('result')[0]
34     except:
35         text = '!@#$%^&^%$#$%^&*'
36     # print(text)
37     return text
ASR.py

分支--图灵机器人配置模块：TuringRobotAPI.py 

 1 '''
 2 图灵机器人API V2.0接入文档：https://www.kancloud.cn/turing/www-tuling123-com/718227
 3 '''
 4 import json
 5 import requests
 6 def turingRobotAnswer(text_question):
 7     request_json={
 8         "perception": { #必须参数：输入信息（注意：输入参数必须包含inputText或inputImage或inputMedia）
 9             "inputText": {          #非必须参数：文本信息
10                 "text": text_question     #必须参数：1-128字符    ，直接输入文本
11             },
12         },
13         "userInfo": {   #必须参数：用户参数
14             "apiKey": "11cb5ce350c54016974151892635388b",   #必须参数：32位，机器人标识
15             "userId": "123"                                 #必须参数：长度小于等于32位，用户唯一标识
16         }
17     }
18     result=requests.post('http://openapi.tuling123.com/openapi/api/v2',json=request_json)#POST请求，参数文档有说明
19     # print(result)
20     text_answer=json.loads(result.content).get('results')[0].get('values').get('text')
21     return text_answer
TuringRobotAPI.py

分支--自然语言处理模块：NLP.py

 1 from aip import AipNlp
 2 from TuringRobotAPI import turingRobotAnswer
 3 
 4 APP_ID = '16815394'
 5 API_KEY = 'jM4b8GIG9gzrzySTRq3szK2E'
 6 SECRET_KEY = 'iE626cEpjT1iAVwh24XV5h1QFuR8FPD2'
 7 
 8 NLP_client = AipNlp(APP_ID, API_KEY, SECRET_KEY)
 9 
10 
11 def nlp(text_question):
12     text_answer = '我是无所不知的智能小机器人飞飞！'
13     score = NLP_client.simnet(text_question, '你叫什么名字').get('score')
14     if score < 0.58:
15         text_answer = turingRobotAnswer(text_question)
16     return text_answer
NLP.py

分支--语音合成模块：TTS.py

 1 import os
 2 
 3 from aip import AipSpeech
 4 
 5 APP_ID = '16815394'
 6 API_KEY = 'jM4b8GIG9gzrzySTRq3szK2E'
 7 SECRET_KEY = 'iE626cEpjT1iAVwh24XV5h1QFuR8FPD2'
 8 
 9 SPEECH_client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
10 
11 # TTS合成语音文件（语音合成）
12 VOICE = {'spd': 5, 'pit': 7, 'vol': 6, 'per': 4, }
13 
14 
15 def tts(text_answer):
16     audio = SPEECH_client.synthesis(text_answer, 'zh', 1, VOICE)
17     from uuid import uuid4
18     answer_filepanme = f'{uuid4()}.mp3'
19     answer_filepath = os.path.join(os.path.dirname(__file__), 'audio', 'answers', answer_filepanme)
20 
21     if not isinstance(audio, dict):
22         with open(answer_filepath, 'wb') as f:
23             f.write(audio)
24 
25     return answer_filepath
TTS.py

分支--语音应答蓝图模块：BP_get_answer.py

 1 import os
 2 from flask import Blueprint, send_file, request
 3 
 4 dir_static = os.path.join('audio', 'answers')
 5 app_get_answer = Blueprint('get_answer', __name__, static_folder=dir_static, static_url_path='/get_answer')
 6 
 7 
 8 @app_get_answer.route('/<filename>')
 9 def get_answer(filename):
10     return send_file(filename)
BP_get_answer.py

 

posted @ 2019-07-17 18:04  笑得好美  阅读(658)  评论(0)  编辑  收藏  举报