AEC_DeepModel

基于深度学习的声学回声消除基线代码

具体解析见我的博客：https://www.cnblogs.com/LXP-Never/p/14779360.html

数据准备

按照以下文件结构，放好语音，我直接使用的是AEC-Challenge 数据集中的合成数据集

└─Synthetic
    ├─TEST
    │  ├─echo_signal
    │  ├─farend_speech
    │  ├─nearend_mic_signal
    │  └─nearend_speech
    ├─TRAIN
    │  ├─echo_signal
    │  ├─farend_speech
    │  ├─nearend_mic_signal
    │  └─nearend_speech
    └─VAL
        ├─echo_signal
        ├─farend_speech
        ├─nearend_mic_signal
        └─nearend_speech

数据处理脚本为 data_preparation.py

如果想要自己生成回声的话建议使用 RIR-Generator 方法，毕竟很多论文中使用的也是这个方法

运行

python train.py

具体的命令行解析参数见train.py脚本

估计近端语音

python test/model_test.py

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我以后还会开源更有价值的内容

参考

语音数据增强及python实现

AEC_DeepModel - Deep learning based acoustic echo cancellation baseline code

Related tags

Overview

AEC_DeepModel

数据准备

运行

估计近端语音

参考

Owner

凌逆战

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