DNN语音增强实现——准备所需分类数据

• 已知：（1）语音数据：包括文件夹speech，noise（训练数据、验证数据及测试数据未分类）；（2）训练数据文本文档speech.txt、验证数据文本文档val.txt、测试数据文本文档core_test192.txt；
• 根据已知创建所需分类数据。
• 具体实现代码：

import os
import soundfile as sf
from Four_DNN_Denoise import config_s
from Four_DNN_Denoise.utils import create_folder, read_audio, write_audio


def data_ready(data_type):
    workspace = config_s.workspace                        # 工作空间
    data_dir = config_s.data_dir                          # premix_data数据目录
    snr = config_s.SNR
    fs = config_s.fs
    tra_speech_filename = os.path.join(workspace,'speech.txt')             # 训练数据（1800条）
    val_speech_filename = os.path.join(workspace, 'val.txt')               # 验证数据（200条）
    core_test192_filename = os.path.join(workspace, 'core_test192.txt')    # 测试数据（192条）
    all_filename = os.path.join(workspace, 'all.txt')                      # 所有数据（2192条）
    speech_dir = os.path.join(data_dir, 'speech')
    noise_dir = os.path.join(data_dir, 'noise')           # 噪声（noise）目录

    noise_name = [na for na in os.listdir(noise_dir) if na.lower().endswith(".wav")]
    print(f'noise_name:{noise_name}')
    if data_type == 'train':
        i = 1
        # 创建训练数据文件夹，存放训练数据
        with open(tra_speech_filename, 'r') as tra_file_to_read:
            # while True:                                # 不能用while True,因为读到最后一行时，为空
            while tra_file_to_read.readline():           # 只要读取的行不为空，则继续
            # for i in range(1, 1800):
                # 读取训练数据

                i += 1
                if i == 1799:
                    print(f'i={i}')
                lines = tra_file_to_read.readline()  # 整行读取数据，也即获取语音数据对应的文件名
                # print(lines)
                tmp = lines.split()[0]  # 去除“\n”
                speech_na_path = os.path.join(data_dir, "speech", "%s.%s" % (tmp, "wav"))     # 语音所在路径
                speech = read_audio(speech_na_path)                                           # 读取语音数据
                tr_speech_path = os.path.join(data_dir, "train_data", "%s.wav" % tmp)         # 定义存放训练数据的文件夹
                create_folder(os.path.dirname(tr_speech_path))                                # 创建存放训练数据的文件夹
                write_audio(tr_speech_path, speech, fs)                                       # 写入语音数据
        tra_file_to_read.close()                                                              # 关闭文件
    elif data_type == 'val':
        # 创建验证数据文件夹，存放验证数据
        with open(val_speech_filename, 'r') as val_file_to_read:
            # while True:
            while val_file_to_read.readline():
            # for i in range(1, 200):
                # 读取验证数据
                lines = val_file_to_read.readline()  # 整行读取数据，也即获取语音数据对应的文件名
                # print(lines)
                tmp = lines.split()[0]  # 去除“\n”
                speech_na_path = os.path.join(data_dir, "speech", "%s.%s" % (tmp, "wav"))
                speech = read_audio(speech_na_path)
                tr_speech_path = os.path.join(data_dir, "val_data", "%s.wav" % tmp)
                create_folder(os.path.dirname(tr_speech_path))
                write_audio(tr_speech_path, speech, fs)
        val_file_to_read.close()
    elif data_type == 'test':
        # 创建测试数据文件夹，存放测试数据
        with open(core_test192_filename, 'r') as tes_file_to_read:
            while tes_file_to_read.readline():
            # for i in range(1, 192):
                line = tes_file_to_read.readline()
                tmp = os.path.splitext(line)[0]                     # 示例：tmp：F:\BaiduNetdiskDownload\TIMIT-wav\TEST\DR1\MDAB0\SI1039
                tmp_ = tmp.split("\\")[6]                           # 示例：tmp_：SI1039
                with open(all_filename, 'r') as all_file_to_read:
                    # for i in range(1, 2192):
                    while all_file_to_read.readline():
                        all_line = all_file_to_read.readline()
                        all_tmp = all_line.split()[0]  # 测试数据的文件名称      # 示例：DR1_FMEM0_SX387
                        all_tmp_ = all_tmp.split("_")[2]                        # 示例：SX387
                        if all_tmp_ == tmp_:
                            # print(all_tmp)
                            tes_na = os.path.join(data_dir, "speech", "%s.wav" % all_tmp)
                            speech = read_audio(tes_na)
                            tes_speech_path = os.path.join(data_dir, "tes_data", "%s.wav" % all_tmp)
                            create_folder(os.path.dirname(tes_speech_path))
                            write_audio(tes_speech_path, speech, fs)

                all_file_to_read.close()
        tes_file_to_read.close()
    else:
        print("Data_type Error!")
    pass

def main():
    data_ready('train')
    data_ready('val')
    data_ready('test')


    pass

if __name__ == '__main__':
    main()