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Show HN: Three new Kitten TTS models – smallest less than 25MB

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Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#141

Good on device TTS is an amazing accessibility tool. Thank you for building this. Way too many of devices that use it rely on online services, this is much preferred.

thanks a lot for the feedback. glad you liked it. we're gonna be launching more tiny models across use-cases.

Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#142

Earlier quoted context omitted.

damnn, lemme fix it, sorry for that. we may have forgotten to remove the redundant dependencies. i'll comment here once i push the change. thanks a lot for trying it and giving feedback.

It's mostly torch, I think. It pulls in NVIDIA libs (which … makes sense, I guess), and NVIDIA is just not at all judicious when it comes to disk space. I literally run out of disk trying to install this on Linux. On macOS, it's a markedly different experience: it's only ~700 MiB there; I'm assuming b/c no NVIDIA libs get pulled in, b/c why would they. For anyone who might want to play around with this: I can get dow…

thanks a lot for sharing this, its v helpful for fixing the env issues. we'll fix all of them by the weekend.

Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#143

Earlier quoted context omitted.

Yes, we've started working on it and will have a range of stt models v soon. lmk if you have a prod use-case in mind?

Many of my use cases are similar to those of: Robert J. P. Oberg - (GitHub) ognistik Perhaps his YouTube channel is worth a watch. This video from four months ago compares various STT tools: https://youtu.be/pKU9CABtnOw Speaking of apps that would, if I had to guess, love to integrate you: FluidVoice is incredible and developing quickly. Handy is really hot right now. Also have VoiceInk out there, solid iOS option. […

got it, this helps a lot. thanks!

Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#145

How did you make a very small AI model (14M) sound more natural and expressive than even bigger models?

glad you liked it, thank you so much for the kind words. our team is really good at squeezing performance out of small models. we are working on a new launch and hope to release a technical report along with that which includes details. fyi, our current 14M model is better than our previous 80M model. and we expect this trend to continue.

Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#147

So, one thing I noticed, and this could easily be user error, is that if I set the text & voice in the example to: text =""" Hello world. This is Kitten TTS. Look, it's working! """ voice = 'Luna' On macOS, I get "Kitten TTS", but on Linux, I get "Kit… TTS". Both OSes generate the same phonemes of, Phonemes: ðɪs ɪz kˈɪʔn ̩ tˌiːtˌiːˈɛs , which makes me really confused as to where it's going off the rails on Linux, sin…

hey sorry for this issue, i think its a bug in our preprocessing. let me look into it and help fix it. i think you posted this in our discord so lets carry the conversation there.

Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#148

Did they train this on @lauriewired's voice? The demo video sounds exactly like her at 0:18

i can confirm that we did not.

What's the source of that voice then in training data? It sounds insanely close to her voice. Strange parallel to openAI denying they trained on Scarlet J's voice.

Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#149

Earlier quoted context omitted.

I don't think so. It is perhaps a bug to have this unnecessary dependency. I expect the author of kitten to fix this soon.

thanks a lot for helping w this. yes i'll fix this asap.

Please let me know when this has been fixed. I will update purr to make the installation steps simpler.

Re: Show HN: Three new Kitten TTS models – smallest less than 25MB

#150

How much work would it be to use the C++ ONNX run-time with this instead of Python? Is it a Claudeable amount of work? The iOS version is Swift-based.

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.

I want to run it in a website with Wasm and having the browser do the audio playback
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