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cloud.google.com·6h ago
AI Research
arXiv CS.AI·Aug 3·5 min read
Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens
TL;DR
A new framework called Locodec enables stable autoregressive speech generation using low-frame-rate, high-dimensional continuous tokens, achieving high fidelity and predictability. This approach mitigates error accumulation during streaming generation, enhancing long-form synthesis quality.
✦ Why It Matters
Consider implementing Locodec for your next speech generation project to enhance output quality and stability.
Key Takeaways
- Explore Locodec for improved speech generation fidelity.
- Utilize MP-ELD to minimize error accumulation in AR models.
- Experiment with 8-Hz, 768-dimensional tokens for better predictability.
- Avoid reliance on external models to streamline your workflow.
How It Works
Locodec shapes its representation space to enhance the interpolatability of a lower-dimensional core manifold, improving the predictability of high-dimensional tokens. The MP-ELD framework uses multi-path information routing and residual classifier-free guidance to effectively manage and reduce error accumulation during the autoregressive generation process.