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We release a technical blog on training PocketTTS, our 100M parameter on-device TTS, through drifting, a recent one-step generative objective from Deng et al. Less than 1% WER, high quality and voice cloning. To the best of our knowledge, it's the first speech model, and the first autoregressive model,...

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kyutai

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17,569 Aufrufe • vor 3 Tagen •via X (Twitter)

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Profilbild von kyutai
kyutaivor 3 Tagen

PocketTTS speaks in continuous latents, one every 80 ms, and a small head turns noise into the next latent in a single forward pass. We used to train with LSD, another one-step flow matching loss, but this required Jacobian-vector products at training time. This is not needed anymore with the drifting recipe.

Profilbild von kyutai
kyutaivor 3 Tagen

The key ingredient we came up with to make it work is a learned kernel temperature. The full write-up with the recipe and all the ablations is here : Code: Original Drifting paper:

Profilbild von Aïna
Aïnavor 3 Tagen

Can I just say this little guy is so cute

Profilbild von LastResort
LastResortvor 3 Tagen

@grok which language it supports?

Profilbild von {stc}
{stc}vor 3 Tagen

nice work playas

Profilbild von Francisco Carlos Erra
Francisco Carlos Erravor 2 Tagen

🙂

Profilbild von Eman Khoubian
Eman Khoubianvor 3 Tagen

less than 1% WER on TTS means a speech recognizer heard the words. it says nothing about whether the cloned voice still sounds right at minute 20, which is where synthetic voices break.

Profilbild von Yazid Janati
Yazid Janativor 3 Tagen

@YentiCollin @samsongvch

Profilbild von Vi VL
Vi VLvor 3 Tagen

Есть поддержка realtime?

Profilbild von mdzor
mdzorvor 3 Tagen

@LocallyAIApp 🙈

Profilbild von semonic
semonicvor 3 Tagen

Awesome i love this project I just wish you guys jad used more and better training data

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