ASRT_SpeechRecognition/test_mspeech.py

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: nl8590687
用于测试语音识别系统语音模型的程序
"""
import platform as plat
import os
import tensorflow as tf
from keras.backend.tensorflow_backend import set_session
from SpeechModel24 import ModelSpeech
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
#进行配置使用70%的GPU
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.9
#config.gpu_options.allow_growth=True #不全部占满显存, 按需分配
set_session(tf.Session(config=config))
datapath = ''
modelpath = 'model_speech'
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 + 'm24\\speech_model24_e_0_step_42500.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)