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 $.ajax({
49 url: serv + "/ai_uploader",
50 type: ‘post‘,
51 processData: false,
52 contentType: false,
53 data: formdata,
54 dataType: ‘json‘,
55 success: function (data) {
56 //console.log(data.filename);
57 var filename = data.filename;
58 document.getElementById(‘player‘).src = serv + ‘/get_answer/‘ + filename;
59 }
60 })
61 });
62
63 reco.clear();
64 }
65
66 </script>
67 </html>
WebToy.html
分支--语音识别：ASR.py
1 import os
2 from aip import AipSpeech
3
4 APP_ID = ‘16815394‘
5 API_KEY = ‘jM4b8GIG9gzrzySTRq3szK2E‘
6 SECRET_KEY = ‘iE626cEpjT1iAVwh24XV5h1QFuR8FPD2‘
7
8 client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
9
10
11 # 读取文件
12 def get_file_content(filepath):
13 # 文件格式转换成pcm(前提是需要安装ffmpeg软件并配置环境变量)
14 filename = os.path.basename(filepath)
15 pcm_filename = filename.split(‘.‘)[0] + ‘.pcm‘
16 pcm_filepath = os.path.join(os.path.dirname(__file__), ‘audio‘, ‘pcm‘, pcm_filename)
17 cmd_str = f‘ffmpeg -y -i {filepath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {pcm_filepath}‘ # ffmpeg软件安装及环境变量配置
18 os.system(cmd_str) # 调用os.system()在CMD执行命令
19 filepath = pcm_filepath
20
21 with open(filepath, ‘rb‘) as fp:
22 return fp.read()
23
24
25 # 识别本地文件
26 def asr(filePath):
27 pcm_file = get_file_content(filePath)
28 result = client.asr(pcm_file, ‘pcm‘, 16000, {
29 ‘dev_pid‘: 1536,
30 })
31 print(result)
32 try:
33 text = result.get(‘result‘)[0]
34 except:
35 text = ‘[email protected]#$%^&^%$#$%^&*‘
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
原文地址：https://www.cnblogs.com/open-yang/p/11202683.html
时间： 2024-10-31 01:56:42