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Reverb Augmentation

See original GitHub issue

Currently supported in torchaudio using sox.

import torch 
import torchaudio
from pyannote.audio.utils.preview import listen
from IPython.display import Audio

x = torchaudio.sox_effects.effect_names()
effects = [["reverb"]]
wave,sr = torchaudio.load("./tests/data/tst00.wav")
display(Audio(wave, rate=sr))
wave, sr = torchaudio.sox_effects.apply_effects_tensor(wave, sr, effects)
print(sr, wave.shape)
display(Audio(wave[0][None], rate=sr))

I found an article where someone implements Schroeder’s Reverberator algorthim and comes with code

Is this something that you are planning to implement/ in the process of doing so?

Issue Analytics

State:
Created 3 years ago
Comments:6 (3 by maintainers)

Top GitHub Comments

3reactions

mparientecommented, Nov 11, 2020

I forgot about this one which would get close to this feature: https://github.com/facebookresearch/denoiser/blob/master/denoiser/augment.py#L29

1reaction

popcornellcommented, Nov 11, 2020

It could be interesting to try, even if simulated RIRs are usually much more realistic than DSP-based artificial reverbs (at least open-source ones, commercial ones are another story). I think it has never been explored and can actually be much faster than convolving with long RIRs.

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