ASRT_SpeechRecognition/train_mspeech.py

70 lines
2.2 KiB
Python
Raw Normal View History

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2016-2099 Ailemon.net
#
# This file is part of ASRT Speech Recognition Tool.
#
# ASRT is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# ASRT is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with ASRT. If not, see <https://www.gnu.org/licenses/>.
# ============================================================================
"""
@author: nl8590687
用于训练语音识别系统语音模型的程序
"""
import platform as plat
import os
import tensorflow as tf
2021-05-16 20:28:20 +08:00
#from keras.backend.tensorflow_backend import set_session
2020-08-10 16:35:40 +08:00
from SpeechModel251 import ModelSpeech, ModelName
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
2018-07-15 14:21:10 +08:00
#进行配置使用95%的GPU
#config = tf.compat.v1.ConfigProto()
#config.gpu_options.per_process_gpu_memory_fraction = 0.95
#config.gpu_options.allow_growth=True #不全部占满显存, 按需分配
#sess = tf.compat.v1.Session(config=config)
#tf.compat.v1.keras.backend.set_session(sess)
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
2020-08-10 16:35:40 +08:00
os.makedirs(modelpath + '/m' + ModelName)
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'):
2020-10-22 20:10:57 +08:00
datapath = 'D:\\SpeechData'
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 + 'speech_model251_e_0_step_327500.h5')
ms.TrainModel(datapath, epoch = 50, batch_size = 16, save_step = 5000)