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adiyoss avatar adiyoss commented on July 17, 2024

The SI-SNRi value that you mentioned (20.1) was reported over the test set (tt), a similar number was also reached for the validation set (cv), and I do not recall the train SI-SNRi numbers (probably a bit better).
Regrading SNR values, you can see all the details in our paper: http://proceedings.mlr.press/v119/nachmani20a/nachmani20a.pdf
Or you can find details on the dataset here: https://enk100.github.io/speaker_separation/

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srdfjy avatar srdfjy commented on July 17, 2024

Hi,Are svoice's experimental results based on "make_dataset.py" to create a noisy data set for training?

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adiyoss avatar adiyoss commented on July 17, 2024

@srdfjy,
In this paper: https://arxiv.org/pdf/2011.02329.pdf the noisy-reverberant data we generated using the make_dataset.py script. In this paper: http://proceedings.mlr.press/v119/nachmani20a/nachmani20a.pdf the dataset was generated using the scripts from this link https://enk100.github.io/speaker_separation/

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srdfjy avatar srdfjy commented on July 17, 2024

thanks @adiyoss

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