asteroid-team / asteroid

The PyTorch-based audio source separation toolkit for researchers

Home Page:https://asteroid-team.github.io/

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Using custom data for model training and testing

leandermaben opened this issue · comments

I need to train and evaluate the ConvTasNet model on speech enhancement for a custom dataset.
How should I go about formatting the data, and what changes need to be made in the run.sh file.

Hey, thanks for the issue !

Have you had a look at already implemented speech enhancement dataset, how do they look like ?

Hi, thanks for the response.
By dataset, I don't mean the dataset class. I mean I want to use my own data ( clean and noisy .wav files) for training instead of wham or any of the other ones.
I was hoping to do this directly using the ConvTasNet recipe by just changing the parameters in run.sh. Would this be possible?

Not directly, not. Unless you create the json file that the WHAM dataset expects for your data, which is quite simple.

Otherwise, you need to create a dataset class for your own data, that's why I suggest you to look at how the datasets are implemented.

Sure, I will look into it.
Thank You.