2018-05-11 18:42:58 +08:00
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#!/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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用于测试语音识别系统语音模型的程序
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"""
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import platform as plat
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import os
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import tensorflow as tf
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from keras.backend.tensorflow_backend import set_session
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2018-07-27 14:31:48 +08:00
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from SpeechModel251 import ModelSpeech
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2018-05-11 18:42:58 +08:00
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os.environ["CUDA_VISIBLE_DEVICES"] = "0"
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2018-07-15 14:21:10 +08:00
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#进行配置，使用90%的GPU
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2020-03-27 05:04:53 +08:00
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config = tf.compat.v1.ConfigProto()
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2018-05-11 18:42:58 +08:00
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config.gpu_options.per_process_gpu_memory_fraction = 0.9
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#config.gpu_options.allow_growth=True #不全部占满显存, 按需分配
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2020-03-27 05:04:53 +08:00
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sess = tf.compat.v1.Session(config=config)
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tf.compat.v1.keras.backend.set_session(sess)
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2018-05-11 18:42:58 +08:00
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datapath = ''
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modelpath = 'model_speech'
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if(not os.path.exists(modelpath)): # 判断保存模型的目录是否存在
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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
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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
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if(system_type == 'Windows'):
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2020-10-22 20:10:57 +08:00
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datapath = 'D:\\SpeechData'
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2018-05-11 18:42:58 +08:00
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modelpath = modelpath + '\\'
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elif(system_type == 'Linux'):
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datapath = 'dataset'
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modelpath = modelpath + '/'
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else:
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print('*[Message] Unknown System\n')
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datapath = 'dataset'
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modelpath = modelpath + '/'
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ms = ModelSpeech(datapath)
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2018-07-27 14:31:48 +08:00
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ms.LoadModel(modelpath + 'm251/speech_model251_e_0_step_42500.model')
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2018-05-11 18:42:58 +08:00
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2018-05-28 17:43:50 +08:00
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ms.TestModel(datapath, str_dataset='test', data_count = 128, out_report = True)
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2018-05-11 18:42:58 +08:00
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#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00241I0053.wav')
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#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00020I0087.wav')
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#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\train\\A11\\A11_167.WAV')
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#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\test\\D4\\D4_750.wav')
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#print('*[提示] 语音识别结果：\n',r)
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