Compatibility with Matcha TTS about vocos HOT 7 OPEN

@mush42 I took a different approach. I searched for the appropriate parameters of torchaudio.transforms.MelSpectrogram to ensure that the features of Vocos match those of Matcha, which are also the same as those of HiFi-GAN

The difference was on the frequency limits and the mel scaling that uses by default torchaudio.

mel_spec_transform_mod = torchaudio.transforms.MelSpectrogram( sample_rate=sample_rate, n_fft=n_fft, hop_length=hop_length, n_mels=n_mels, center=padding == "center", power=1, f_min=0, f_max=8000, norm="slaney", mel_scale="slaney", )

I also updated the feature extraction in the reconstruction loss. You can check the changes in this fork https://github.com/wetdog/vocos/tree/matcha

The results sound good after 20 epochs with Libritts, We'll publish the checkpoints once the training finishes.

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@hubertsiuzdak @alealv

would you mind helping with this? I don't know where to start.

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@mush42 Hey, I'm pissing around with the same thing currently.

Tried synthesising using vocos as a head to MatchaTTS. Vocos seems to want 100 mel bins? Matcha currently outputs specs with 80bins. I'm not sure the best way to go, either retrain Matcha on 100bins, or see if zero padding could work. I tried earlier, just zero padding from 80 to 100mel bins, and synthesising through vocos mel head, quality wasn't that great

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You can check out my fork with config for 22050 vocos - https://github.com/egorsmkv/vocos

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@egorsmkv, even after training the model with vocos.yaml config from your repo, the issue seems to persist, the output is still robotic and in low-volume

@hubertsiuzdak @alealv, Any help or guidance regarding this would be really helpful!

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@egorsmkv, even after training the model with vocos.yaml config from your repo, the issue seems to persist, the output is still robotic and in low-volume

@hubertsiuzdak @alealv, Any help or guidance regarding this would be really helpful!

How many steps did you train?

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How many steps did you train?

15k steps

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