Comments (4)
adiyoss
commented on August 16, 2024
Hi @Turan111,
I think it depends on you task. Do you want to model the noise too or not?
In our case, since we were only interested in the clean and separated signals, we simply ignored the noise and predicted the clean signals only. That way the model is both separating and denoising.
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Turan111
commented on August 16, 2024
Hi @adiyoss ,
Many thanks for the responce,
I don't want to model noise, but I am interested in the clean and separated human voice. In this case which approach gives better results? Have you done such experiment?
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adiyoss
commented on August 16, 2024
@Turan111
Yes, so we did experiment with training on noisy (w./wo. reverb) mixtures and predicting the clean separated channels. We experimented with WHAM! and WHAMR! benchmarks (http://wham.whisper.ai/).
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adiyoss
commented on August 16, 2024
Closing this issue for now. Feel free to reopen in case you have more questions! :)
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