132 lines
2.9 KiB
Python
132 lines
2.9 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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@author: nl8590687
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语音识别API的HTTP服务器程序
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"""
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import http.server
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import urllib
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import keras
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from SpeechModel24 import ModelSpeech
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from LanguageModel import ModelLanguage
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datapath = 'data/'
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modelpath = 'model_speech/'
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ms = ModelSpeech(datapath)
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ms.LoadModel(modelpath + 'm24/speech_model24_e_0_step_411000.model')
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ml = ModelLanguage('model_language')
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ml.LoadModel()
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class TestHTTPHandle(http.server.BaseHTTPRequestHandler):
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def _set_response(self):
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self.send_response(200)
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self.send_header('Content-type', 'text/html')
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self.end_headers()
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def do_GET(self):
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buf = 'ASRT_SpeechRecognition API'
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self.protocal_version = 'HTTP/1.1'
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self._set_response()
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buf = bytes(buf,encoding="utf-8")
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self.wfile.write(buf)
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def do_POST(self):
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'''
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处理通过POST方式传递过来并接收的语音数据
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通过语音模型和语言模型计算得到语音识别结果并返回
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'''
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path = self.path
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print(path)
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#获取post提交的数据
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datas = self.rfile.read(int(self.headers['content-length']))
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#datas = urllib.unquote(datas).decode("utf-8", 'ignore')
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datas = datas.decode('utf-8')
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datas_split = datas.split('&')
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token = ''
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fs = 0
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wavs = []
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#type = 'wavfilebytes' # wavfilebytes or python-list
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for line in datas_split:
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[key, value]=line.split('=')
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if('wavs' == key and '' != value):
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wavs.append(int(value))
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elif('fs' == key):
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fs = int(value)
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elif('token' == key ):
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token = value
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#elif('type' == key):
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# type = value
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else:
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print(key, value)
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if(token != 'qwertasd'):
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buf = '403'
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print(buf)
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buf = bytes(buf,encoding="utf-8")
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self.wfile.write(buf)
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return
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#if('python-list' == type):
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if(len(wavs)>0):
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r = self.recognize([wavs], fs)
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else:
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r = ''
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#else:
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# r = self.recognize_from_file('')
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if(token == 'qwertasd'):
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#buf = '成功\n'+'wavs:\n'+str(wavs)+'\nfs:\n'+str(fs)
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buf = r
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else:
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buf = '403'
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#print(datas)
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self._set_response()
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#buf = '<!DOCTYPE HTML> \n<html> \n<head>\n<title>Post page</title>\n</head> \n<body>Post Data:%s <br />Path:%s\n</body> \n</html>'%(datas,self.path)
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print(buf)
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buf = bytes(buf,encoding="utf-8")
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self.wfile.write(buf)
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def recognize(self, wavs, fs):
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r=''
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try:
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r_speech = ms.RecognizeSpeech(wavs, fs)
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print(r_speech)
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str_pinyin = r_speech
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r = ml.SpeechToText(str_pinyin)
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except:
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r=''
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print('[*Message] Server raise a bug. ')
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return r
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pass
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def recognize_from_file(self, filename):
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pass
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def start_server(ip, port):
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http_server = http.server.HTTPServer((ip, int(port)), TestHTTPHandle)
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print('服务器已开启')
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try:
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http_server.serve_forever() #设置一直监听并接收请求
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except KeyboardInterrupt:
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pass
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http_server.server_close()
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print('HTTP server closed')
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if __name__ == '__main__':
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start_server('', 20000)
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