def recognize(self, wavs, fs): datapath = 'data/' modelpath = 'model_speech/' ms = ModelSpeech(datapath) ms.LoadModel(modelpath + 'speech_model22_e_0_step_6500.model') r_speech = ms.RecognizeSpeech(wavs, fs) ml = ModelLanguage('model_language') ml.LoadModel() str_pinyin = r_speech r = ml.SpeechToText(str_pinyin) return r pass
system_type = plat.system() # 由于不同的系统的文件路径表示不一样,需要进行判断 if (system_type == 'Windows'): datapath = 'E:\\语音数据集' modelpath = modelpath + '\\' elif (system_type == 'Linux'): datapath = 'dataset' modelpath = modelpath + '/' else: print('*[Message] Unknown System\n') datapath = 'dataset' modelpath = modelpath + '/' ms = ModelSpeech(datapath) #ms.LoadModel(modelpath + 'm22_2\\0\\speech_model22_e_0_step_257000.model') ms.LoadModel(modelpath + 'm22_2/0/speech_model22_e_0_step_257000.model') #ms.TestModel(datapath, str_dataset='test', data_count = 64, out_report = True) r = ms.RecognizeSpeech_FromFile( 'E:\语音数据集\ST-CMDS-20170001_1-OS\\20170001P00241I0052.wav') #r = ms.RecognizeSpeech_FromFile('E:\\VS2015解决方案\\wav文件读写样例\\wav文件读写样例\\bin\\Debug\\1.wav') #r = ms.RecognizeSpeech_FromFile('/home/nl/01.wav') #r = ms.RecognizeSpeech_FromFile('C:\\Users\\nl\\Desktop\\01.wav') #r = ms.RecognizeSpeech_FromFile('E:\语音数据集\ST-CMDS-20170001_1-OS\\20170001P00241I0053.wav') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00020I0087.wav') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\train\\A11\\A11_167.WAV') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\test\\D4\\D4_750.wav') print('*[提示] 语音识别结果:\n', r) ml = ModelLanguage('model_language') ml.LoadModel()
system_type = plat.system() # 由于不同的系统的文件路径表示不一样,需要进行判断 if (system_type == 'Windows'): datapath = 'E:\\语音数据集' modelpath = modelpath + '\\' elif (system_type == 'Linux'): datapath = 'dataset' modelpath = modelpath + '/' else: print('*[Message] Unknown System\n') datapath = 'dataset' modelpath = modelpath + '/' ms = ModelSpeech(datapath) ms.LoadModel(modelpath + 'm22\\speech_model22_e_0_step_6500.model') #ms.TestModel(datapath, str_dataset='test', data_count = 64, out_report = True) r = ms.RecognizeSpeech_FromFile( 'E:\语音数据集\ST-CMDS\ST-CMDS-20170001_1-OS\\20170001P00241I0052.wav') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\train\\A11\\A11_167.WAV') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\test\\D4\\D4_750.wav') print('*[提示] 语音识别结果:\n', r) ml = ModelLanguage('model_language') ml.LoadModel() #str_pinyin = ['zhe4','zhen1','shi4','ji2', 'hao3','de5'] #str_pinyin = ['jin1', 'tian1', 'shi4', 'xing1', 'qi1', 'san1'] #str_pinyin = ['ni3', 'hao3','a1'] str_pinyin = r
if(not os.path.exists(modelpath)): # 判断保存模型的目录是否存在 os.makedirs(modelpath) # 如果不存在,就新建一个,避免之后保存模型的时候炸掉 system_type = plat.system() # 由于不同的系统的文件路径表示不一样,需要进行判断 if(system_type == 'Windows'): datapath = 'E:\\语音数据集' modelpath = modelpath + '\\' elif(system_type == 'Linux'): datapath = 'dataset' modelpath = modelpath + '/' else: print('*[Message] Unknown System\n') datapath = 'dataset' modelpath = modelpath + '/' ms = ModelSpeech(datapath) ms.LoadModel(modelpath + 'm22_2\\2\\speech_model22_e_0_step_123500.model') ms.TestModel(datapath, str_dataset='test', data_count = 128, out_report = True) #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00241I0053.wav') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00020I0087.wav') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\train\\A11\\A11_167.WAV') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\test\\D4\\D4_750.wav') #print('*[提示] 语音识别结果:\n',r)
system_type = plat.system() # 由于不同的系统的文件路径表示不一样,需要进行判断 if (system_type == 'Windows'): datapath = 'E:\\语音数据集' modelpath = modelpath + '\\' elif (system_type == 'Linux'): datapath = 'dataset' modelpath = modelpath + '/' else: print('*[Message] Unknown System\n') datapath = 'dataset' modelpath = modelpath + '/' ms = ModelSpeech(datapath) #ms.LoadModel(modelpath + 'm22_2\\0\\speech_model22_e_0_step_257000.model') ms.LoadModel(modelpath + 'speech_model22_e_0_step_317000.model') #ms.TestModel(datapath, str_dataset='test', data_count = 64, out_report = True) #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00241I0052.wav') #r = ms.RecognizeSpeech_FromFile('E:\语音数据集\ST-CMDS-20170001_1-OS\\20170001P00241I0053.wav') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00020I0087.wav') #r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\train\\A11\\A11_167.WAV') r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\test\\D4\\D4_750.wav') print('*[提示] 语音识别结果:\n', r) ml = ModelLanguage('model_language') ml.LoadModel() #str_pinyin = ['zhe4','zhen1','shi4','ji2', 'hao3','de5'] #str_pinyin = ['jin1', 'tian1', 'shi4', 'xing1', 'qi1', 'san1'] #str_pinyin = ['ni3', 'hao3','a1']
# -*- coding: utf-8 -*- """ @author: nl8590687 语音识别API的HTTP服务器程序 """ import http.server import urllib import keras from SpeechModel22 import ModelSpeech from LanguageModel import ModelLanguage datapath = 'data/' modelpath = 'model_speech/' ms = ModelSpeech(datapath) ms.LoadModel(modelpath + 'speech_model22_e_0_step_216500.model') ml = ModelLanguage('model_language') ml.LoadModel() class TestHTTPHandle(http.server.BaseHTTPRequestHandler): def _set_response(self): self.send_response(200) self.send_header('Content-type', 'text/html') self.end_headers() def do_GET(self): buf = 'ASRT_SpeechRecognition API' self.protocal_version = 'HTTP/1.1'