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View Code? Open in Web Editor NEW基于深度学习的声学回声消除基线代码
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关于训练目标-近端语音的选择
你好，非常谢谢你详细的工作。
在看完你的blog后，我有个问题，计算IRM的近端语音信号，是纯干净的近端语音，还是带噪声带混响的近端语音？ 我尝试使用纯干净的近端语音后没有得到好的loss结果。
感谢任何建议。 @LXP-Never
aec数据前准备
最近我在做aec数据的前准备工作，
aec-challenge, 1万条太少了
我认为可以写一个脚本来用开源数据来制造仿真数据,就如汪德亮老师那篇写的
然后最近有几篇dnn-aec用了aec-challenge的farend数据去做增强仿真，但我觉得这个也只是制标不治本，
我希望的是从timit或者aishell仿真出来．
你看有没有兴趣到时候review一下？
mask 方法提取出来还有部分回声
mask的方法我听了一下你的测试音频里面，是去除了绝大部分的回声，但是近端说话的时候，还是能从背景中听到回声
能不能添加一些数据扩增的方法？
@LXP-Never
大佬，现在回声消除数据集太少了，AEC challenge 里面又没有synthetic 数据合成的脚本，大佬能完善一个吗？谢谢！
关于near end数据加噪声问题
aec挑战赛的数据集中，合成数据集中，near end数据有些是带噪声的，这就意味着将无噪声的near end数据作为训练目标的话，神经网络实际上还需要承担降噪的任务。这合理吗？
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