Kyutai STT & TTS - A Perfect Local Voice Solution? Introduction & Background 00:00
The video reintroduces "Moshi," previously discussed in an earlier review, focusing on its low-latency integration of ASR (Automatic Speech Recognition) and TTS (Text-to-Speech).
Initial impressions of the earlier Moshi model noted low latency but found the language model responses limited in capability.
Kyutai STT & TTS Overview 00:41
Kyutai has now released both speech-to-text (STT) and text-to-speech (TTS) models, supporting only English and French at this stage.
The STT model quickly and accurately transcribes English and French speech.
The TTS model offers multiple voices and is based on a 1.6-billion-parameter model, providing high-quality, quick voice synthesis.
Model Performance & Voice Cloning 01:54
TTS is compared to Chatterbox, Dier, and Eleven Labs, with Kyutai's model performing at a similar high level.
The system can condition TTS on a 10-second voice sample, enabling convincing voice cloning and accurate intonation mimicry.
The model achieves fast and effective voice cloning even with unique or unusual voice samples.
Limitations and Voice Embedding Access 02:52
The actual voice embedding model for custom voice cloning is not released, aiming to prevent non-consensual voice cloning.
Instead, Kyutai provides a repository of voice embeddings sourced from public datasets like Espresso and VCTK.
Fine-tuning for other languages is not currently possible, but exploration of this capability is mentioned.
Accessing and Using the Models 03:53
Both STT and TTS models are available on Hugging Face, including an MLX version of STT for experimentation.
The TTS model was trained on 2.5 million hours of data, more than some recent competitors, and labeled using a Whisper Media model.
Users can select from pre-made voices available as audio files and safe tensor embeddings via provided libraries.
Implementation & Example Code 05:11
The video demonstrates using code from Kyutai’s GitHub to generate speech, allowing selection and application of different pre-made voice embeddings.
The system does not enable custom voice cloning but allows use of pre-supplied embeddings for generating speech in multiple voices.
Voice embeddings are loaded as safe tensor files, and audio samples demonstrate the system’s voice synthesis quality.
Voice Embedding Manipulation 07:12
The video showcases loading and analyzing safe tensor embeddings in PyTorch, including checking embedding dimensionality.
Demonstrates blending two different voice embeddings to create a new, intermediate voice profile.
Highlights that effective blending requires many samples, and the primary limitation remains lack of access to the full voice cloning model.
Overall Assessment & Use Cases 09:03
Kyutai provides capable, lightweight models for both TTS and ASR suitable for local use, with notable performance.
Potential exists to integrate a language model between STT and TTS for a locally run chat system.
Further interest is expressed in an MLX version for Mac compatibility and the hope for eventual release of full voice cloning capabilities.
Viewers are encouraged to experiment with the released resources and share feedback.