Speech-enhancement
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Denoise Pretrained Model and norm_noisy.mat
Two questions here for some help:
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We tried to use the pre-trained model
/backup/TSN.pdto denoise the noisy audios. The results so far have large amount of added white noise in it. Here is an example: the input audio is noisy01_snr03_num0001.raw And the below enhanced audio has a lot of added white noise enhanced01_snr03_num0002.wav Have anyone used the pre-trained models to enhance noisy audios successfully? If so, can you point us what we might be doing wrong? -
What
norm_noisy.matshould be used for testing/inference? The code suggests thenorm_noisy.matis from the training data. If so, can you share thenorm_noisy.matfor the pre-trained model?
Any advice is appreciated! @jtkim-kaist @MayMiao0923 @yangz-zju @ucasiggcas
Same question
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Did you try to use the test code in test_small.py?
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norm_noisy.mat is very important in this code, which means the mean & variance of whole training set. norm_noisy is used to reconstruct the wav from predicted spectrogram. You can make norm_noisy.mat from get_norm.py as described in readme. But if you cannot make cause of any reason, I will upload my own but it will be slightly different from the one of your training dataset.