Data simulation and augmentation

[v-nhandt21]

Can you detail the way you are using to make the noise audio for training?

Does it the same with described in the paper?

Are you using kaldi or any tool for this, and can you share your noise dataset !

Thank rishikksh !

[LXnn058]

Hi, have you solved this problem?

[v-nhandt21]

Hi, have you solved this problem?

With my experiment, the data augmented with Kaldi give better results than some methods that augment on the fly

[LXnn058]

Are the parameters the same as those set in the paper? Can you provide me the corresponding processing script? thanks.

[v-nhandt21]

I think the parameter depending on the test set / practical problem you want to solve.

My config is SNR between 10dB and 30dB, use MUSAN as additive noise

You can check out the public source code here: https://github.com/zhaoyi2/audio_augment

[LXnn058]

This helped me a lot, thanks！

[skol101]

@v-nhandt21 I simply added audiomentations (RoomSimulator, Backgroundnoise) and stored to separate directory, which I use in "input_wavs" params after step for postnet training (250k in my case, though it's 500k in the default config).

[v-nhandt21]

@v-nhandt21 I simply added audiomentations (RoomSimulator, Backgroundnoise) and stored to separate directory, which I use in "input_wavs" params after step for postnet training (250k in my case, though it's 500k in the default config).

Yep, it seems hard for the model to converge on the fly augmentation

[velonica0]

Hi, have you solved this problem?

With my experiment, the data augmented with Kaldi give better results than some methods that augment on the fly

Hi, Bro
Can I get a copy of your processed training data about this code, I don't understand the specific definitions of the folders and file trees in the code, such as gt_noise, gt_clean, generated, etc.