yeah we'll add some more professional-sounding voices and also support for diy custom voices. we tried to add more anime/cartoon-ish voices to showcase the expressivity.

Regarding running on the 3080 gpu, can you share more details on github issues, discord or email? it should be blazing fast on that. i'll add an example to run the model on gpu too.

yes, our mobile sdk is coming soon(eta 2 weeks) so we should be able to replace the built-in version of it. can you share what tts use-case you're thinking of?

thanks a lot, our voice cloning model will be out by May. we're experimenting w some very cool ways of doing voice cloning at 15M but will have a range of models going upto 500M

great idea, let me add this. meanwhile, you can try the models on our huggingface spaces demo here: https://huggingface.co/spaces/KittenML/KittenTTS-Demo

thanks for the feedback. i'll add an example of running it on gpu.

small models struggle with prosody due to limited capacity. this version does much better than the precious one and is the best among other <25MB models. Kokoro is a really good model for its size, its competitive on artificial analysis too. i think by the next release we should have something kokoro quality but a fifth of the size. Adding control for rhythm seems to be quite important too, and we should start looking at that for other languages.

That, and also using English words in the middle of another language phrase confuses them a lot.

thank you so much. Right now, it cannot handle expressive tags. what kind of tags would be most helpful according to you?

yes, we just started working on this yesterday haha, great that you mentioned it. once we have it working it'll be out soon.

80M model is the highest quality while also being quite efficient. it is superior in terms of pronunciation accuracy for less common words, and also is more stable in terms of speed. its my fav model. i think the 40M is quite similar to 80M for most usecases. 15M is for resource cpus, loading onto a browser etc.

The new 15M is way better than the previous 80M model(v0.1). So we're able to predictably improve the quality which is very encouraging.

great idea, we're on it. we're also working on a mobile sdk. a browser sdk would be really cool too.

thanks a lot. small model quality is improving exponentially. This 15M is way better than the 80M model from our previous launch (V0.1).

Any recommendations?

Running the example is 3 MiB for the repo, +667 MiB of Python dependencies, +86 MiB of models that will get downloaded from HuggingFace. =756 MiB.

(That's using the example as-is. If you switch it to the smaller model, modify the above with +57 MiB of models from HuggingFace, or =727 MiB.)

My quick test showed 670m of python libraries required on top of the model.

You need to provide info on your hardware. Pocket-TTS does cloning on CPU, but for me randomly outputs something pretty weird sounding mixed in with like 90% good outputs. So it hasn't been quite stable enough to run without checking output. But maybe it depends on your voice sample.

Qwen 3 TTS is good for voice cloning but requires GPU of some sort.

Is it not just to train a model on your voice recordings and just use that to generate audio clips from text?

I think I tried on my Android everything I could try and 1. outside webpage reading, not many options; 2. as browser extensions, also not many (I don't like to copy URLs in your app) 3. they all insist reading every little shit, not only buttons but also "wave arrow pointing directly right" which some people use in their texts. So basically reading text aloud is a bunch of shitty options. Anyone jumping in this market opening?

thanks, glad you liked it

shouldn't be hard. what backend/hardware are you interested in running this with? i'll add an example for using C++ onnx model. btw check out roadmap, our inference engine will be out 1-2 weeks and it is expected to be faster than onnx.

yes, we're releasing an official mobile sdk and inference engine very soon. if you want to use something until then, some folks from the oss community have built ways to run kitten on ios. if you search kittentts ios on github you should find a few. if you cant find it, feel free to ping me and i can help you set it up. thanks a lot for your support and feedback!

thanks a lot for the feedback. yes, we're working on a diy way to add custom voices and will also be releasing a model with more professional voices in the next 2-3 weeks. as of now, we're providing commercial support for custom voices, languages and deployment through the support form on our github. can you share more about your business use-case? if possible, i'd like to ensure the next release can serve that.

as of now its english only. the training for multilingual model is underway and should be out in April! what languages are you most interested in? Right now, we are providing deployments for custom languages + voices through support form on the github.

it'd be an interesting experiment to try what kind of information is extracted from the samples of the pet sounds. it'd be so cool if it can just get the features of the audio and then still be able to reproduce the audio in english lol. we would need a really good "speaker" encoder i think.