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transformer based neural network for speech enhancement in time domain

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Hello. Sorry, I didn't have any other way of communication, that's why I messaged here. I had a question about the CPTNN article. Is it possible to put the code...

file_name = 'psquare_17.5' test_file_list_path = '/media/concordia/DATA/KaiWang/pytorch_learn/pytorch_for_speech/voice_bank/Transformer/v5/test_file_break' + '/' + file_name audio_file_save = '/media/concordia/DATA/KaiWang/pytorch_learn/pytorch_for_speech/voice_bank/Transformer/v5/audio_file' + '/' + 'enhanced_' + file_name 这里file_name以及test_file_list_path不太懂是什么意思诶

Hello, I want to ask what's the input of the test.py ? .wav ?

您好,想问一下如果用的数据集不是您所用的那个的话,日志文件以及路径要怎么写呢

In the TSTNN paper, the two-stage transformer block passes the input into a local transformer followed by a global transformer. This means that the sequence length (in [here](https://pytorch.org/docs/stable/generated/torch.nn.MultiheadAttention.html)) for the...

Hello, these unorganized files are very unfriendly to me. I want to reproduce your experimental results. Can you write the purpose of these files in readme.txt. thanks!

Hello, Kudos for your work. We would like to have a pre-trained model which can reproduce the results quoted in the paper. Thanks in advance.

您好,想请问一下您的模型大小大概是多大呢?谢谢

Can you share the download link of your dataset?

请问您这套模型的实时性怎么样呢?