Show HN: Three new Kitten TTS models – smallest less than 25MB (github.com)
Today we're releasing three new models with 80M, 40M and 14M parameters.
The largest model (80M) has the highest quality. The 14M variant reaches new SOTA in expressivity among similar sized models, despite being <25MB in size. This release is a major upgrade from the previous one and supports English text-to-speech applications in eight voices: four male and four female.
Here's a short demo: https://www.youtube.com/watch?v=ge3u5qblqZA.
Most models are quantized to int8 + fp16, and they use ONNX for runtime. Our models are designed to run anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! This release aims to bridge the gap between on-device and cloud models for tts applications. Multi-lingual model release is coming soon.
On-device AI is bottlenecked by one thing: a lack of tiny models that actually perform. Our goal is to open-source more models to run production-ready voice agents and apps entirely on-device.
We would love your feedback!
75 comments
[ 3.8 ms ] story [ 76.0 ms ] threadIs there any way to get those running on iPhone ? I would love to have the ability for it to read articles to me like a podcast.
Is there any way to do a custom voice as a DIY? Or we need to go through you? If so, would you consider making a pricing page for purchasing a license/alternative voice? All but one of the voices are unusable in a business context.
Either in the form of the api via pitch/speed/volume controls, for more deterministic controls.
Or in expressive tags such as [coughs], [urgently], or [laughs in melodic ascending and descending arpeggiated gibberish babbles].
the 25MB model is amazingly good for being 25MB. How does it handle expressive tags?
I'm impressed with the quality given the size. I don't love the voices, but it's not bad. Running on an intel 9700 CPU, it's about 1.5x realtime using the 80M model. It wasn't any faster running on a 3080 GPU though.
The iOS version is Swift-based.
If the author doesn't describe some detail about the data, training, or a novel architecture, etc, I only assume they just took another one, do a little finetuning, and repackage as a new product.
Tldr: generate human-like voice based on animal sound. Anyway maybe it doesn't make sense.
Kokoro TTS for example has a very good Norwegian voice but the rhythm and emphasizing is often so out of whack the generated speech is almost incomprehensible.
Haven't had time to check this model out yet, how does it fare here? What's needed to improve the models in this area now that the voice part is more or less solved?
I want to be my own personal assistant...
EDIT: I can provide it a RTX 3080ti.
I couldn't locate how to run it on a GPU anywhere in the repo.