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Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model (github.com)

1003 points by divamgupta ↗ HN
Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters.

This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required!

We're releasing this to give early users a sense of the latency and voices that will be available in our next release (hopefully next week). We'd love your feedback! Just FYI, this model is an early checkpoint trained on less than 10% of our total data.

We started working on this because existing expressive OSS models require big GPUs to run them on-device and the cloud alternatives are too expensive for high frequency use. We think there's a need for frontier open-source models that are tiny enough to run on edge devices!

110 comments

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nine_k
I hope this is the future. Offline, small ML models, running inference on ubiquitous, inexpensive hardware. Models that are easy to integrate into other things, into devices and apps, and even to drive from other models maybe.
discardedrefuse
Hmm. A pay once (or not at all) model that can run on anything? Or a subscription model that locks you in, and requires hardware that only the richest megacorps can afford? I wonder which one will win out.
mayli
Is this english only?
numpad0
TTS is generally not multilingual. One might think a well-annotated phonetic descriptions of voices would suffice, but that's not quite how languages work nor how TTS work.

(but somehow LLMs handle multilingual input perfectly fine! that's a bit strange, if you think about that)

toisanji
Wow, amazing and good work, I hope to see more amazing models running on CPUs!
onair4you
Okay, lots of details information and example code, great. But skimming through I didn’t see any audio samples to judge the quality?
blopker
Web version: https://clowerweb.github.io/kitten-tts-web-demo/

It sounds ok, but impressive for the size.

Jotalea
Using male voice 2 at 48kHz at 0.5x speed sounds a lot like Madeline's voice lines in Celeste. Seemed funny to me.
rldjbpin
besides issues with webgpu (it is in beta fwiw), it'd be nice to increase voice speed through the setting without affecting the voice pitch.
pkaye
Where does the training data come for the models? Is there an openly available dataset the people use?
wewewedxfgdf
say is only 193K on MacOS

  ls -lah /usr/bin/say
  -rwxr-xr-x  1 root  wheel   193K 15 Nov  2024 /usr/bin/say
Usage:

  M1-Mac-mini ~ % say "hello world this is the kitten TTS model speaking"
a96
If you make a shell script that calls say, that script will be even smaller!
RobKohr
What's a good one in reverse; speech to text?
wkat4242
Hmm the quality is not so impressive. I'm looking for a really naturally sounding model. Not very happy with piper/kokoro, XTTS was a bit complex to set up.

For STT whisper is really amazing. But I miss a good TTS. And I don't mind throwing GPU power at it. But anyway. this isn't it either, this sounds worse than kokoro.

andai
Can you run it in reverse for speech recognition?
keyle
I don't mind so much the size in MB, the fact that it's pure CPU and the quality, what I do mind however is the latency. I hope it's fast.

Aside: Are there any models for understanding voice to text, fully offline, without training?

I will be very impressed when we will be able to have a conversation with an AI at a natural rate and not "probe, space, response"

sandreas
Cool.

While I think this is indeed impressive and has a specific use case (e.g. in the embedded sector), I'm not totally convinced that the quality is good enough to replace bigger models.

With fish-speech[1] and f5-tts[2] there are at least 2 open source models pushing the quality limits of offline text-to-speech. I tested F5-TTS with an old NVidia 1660 (6GB VRAM) and it worked ok-ish, so running it on a little more modern hardware will not cost you a fortune and produce MUCH higher quality with multi-language and zero-shot support.

For Android there is SherpaTTS[3], which plays pretty well with most TTS Applications.

1: https://github.com/fishaudio/fish-speech

2: https://github.com/SWivid/F5-TTS

3: https://github.com/woheller69/ttsengine

nickpsecurity
Fish Speech says its weights are for non-commercial use.

Also, what are the two's VRAM requirents? This model has 15 million parameters which might run on low-power, sub-$100 computers with up-to-date software. Your hardware was an out-of-date 6GB GPU.

maxloh
Hi. Will the training and fine-tuning code also be released?

It would be great if the training data were released too!

MutedEstate45
The headline feature isn’t the 25 MB footprint alone. It’s that KittenTTS is Apache-2.0. That combo means you can embed a fully offline voice in Pi Zero-class hardware or even battery-powered toys without worrying about GPUs, cloud calls, or restrictive licenses. In one stroke it turns voice everywhere from a hardware/licensing problem into a packaging problem. Quality tweaks can come later; unlocking that deployment tier is the real game-changer.
CyberDildonics
The github just has a few KB of python that looks like an install script. How is this used from C++ ?
[deleted]
(comment deleted)
Narishma
But Pi Zero has a GPU, so why not make use of it?
a96
Because then you're stuck on that device only.
ethan_smith
This opens up voice interfaces for medical devices, offline language learning tools, and accessibility gadgets for the visually impaired - all markets where cloud dependency and proprietary licenses were showstoppers.
OfflineSergio
amazing! can't wait to integrate it into https://desktop.with.audio I'm already using KokorosTTS without a GPU. It works fairly well on Apple Silicon.

Foundational tools like this open up the possiblity of one-time payment or even free tools.

dang
Most of these comments were originally posted to a different thread (https://news.ycombinator.com/item?id=44806543). I've moved them hither because on HN we always prefer to give the project creators credit for their work.

(it does however explain how many of these comments are older than the thread they are now children of)

righthand
The sample rate does more than change the quality.