alt.hn

3/19/2026 at 3:56:06 PM

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

 https://github.com/KittenML/KittenTTS

by rohan_joshi

3/20/2026 at 12:04:39 AM

I created a CLI wrapper for Kitten TTS: https://github.com/newptcai/purr

BTW, it seems that kitten (the Python package) has the following chain of dependencies: kittentts → misaki[en] → spacy-curated-transformers

So if you install it directly via uv, it will pull torch and NVIDIA CUDA packages (several GB), which are not needed to run kitten.

by dawdler-purge

3/20/2026 at 12:22:17 AM

Thanks, your install script worked for me.

In case it helps anyone else, the first time I tried to run purr I got "OSError: PortAudio library not found". Installing libportaudio (apt install libportaudio2) got it running.

by cristoperb

3/20/2026 at 5:52:41 AM

Also did create a cli. I had to fork the project and removed one unused import which allowed me to remove a lot of unused ml libraries: https://github.com/Mic92/puss-say

by Mic92

3/20/2026 at 5:53:46 AM

Unfortunately upstream never looks at any pull requests.

by Mic92

3/20/2026 at 3:44:35 PM

You might also like CopySpeak, a lightweight tool I've recently built for quick AI text-to-speech using the clipboard, featuring Kitten TTS and other engines.

https://github.com/ilyaizen/CopySpeak

by ilyaizen

3/20/2026 at 12:24:47 AM

Thank you so much, that fixes an enormous pain point I was hitting. It's not just the size, that dependency chain was actually breaking on my machine and failing to install. Are we losing something by dropping the extra dependencies?

by yjftsjthsd-h

3/20/2026 at 1:19:01 AM

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.

by dawdler-purge

3/20/2026 at 3:41:55 AM

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

by rohan_joshi

3/20/2026 at 4:28:10 AM

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

by dawdler-purge

3/19/2026 at 4:40:41 PM

What I love about OpenClaw is that I was able to send it a message on Discord with just this github URL and it started sending me voice messages using it within a few minutes. It also gave me a bunch of different benchmarks and sample audio.

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.

by kevin42

3/19/2026 at 5:00:52 PM

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.

by rohan_joshi

3/20/2026 at 2:57:39 AM

I wonder if it's possible to guide the intonation in any way.

by nine_k

3/19/2026 at 8:49:18 PM

Oh that is a good use case. Don't connect to email and all that insecure stuff. But as a sandbox for "try this out and deploy a demo". Got me thinking!

by nsnzjznzbx

3/20/2026 at 12:19:46 AM

I'm jealous. It took me far longer and much more frustration to get it to run.

Had to get the right Python version and make sure it didn't break anything with the previous Python version. A friend suggested using Docker, so I started down that path until I realized I'd probably have to set the whole thing up there myself. Eventually got it to run and I think I didn't break anything else.

I hate Python so much.

by Aerroon

3/20/2026 at 2:46:29 AM

Nowadays these frustrations shouldn't be a thing any more. If the author used uv, the script would be able to install its own dependencies and just work.

by stavros

3/20/2026 at 3:59:40 AM

yeah let me add uv and conda support to make it easier.

by rohan_joshi

3/20/2026 at 8:26:43 PM

Thanks! I asked my bot to make me a plugin for it and it one-shotted it, the resulting script was ~20 lines, very nice!

by stavros

3/20/2026 at 7:13:20 AM

One of the most responsive developers I’ve ever seen, kudos

by Barbing

3/20/2026 at 12:32:21 AM

why you don't use some kind of environment, Conda or something like that?

by RobertoG

3/20/2026 at 1:47:12 AM

I used uv, which should have generated a stable environment. No dice. There's a bug in spacey.

I suspect success is highly variable on macOS vs. Linux; the spacey bug is only in newer (3.14 only or later) Pythons, which Linux will have.

by deathanatos

3/20/2026 at 4:01:11 AM

thanks for pointing these errors out. we're looking into this and will help fix this.

by rohan_joshi

3/20/2026 at 1:39:05 AM

Even the built in venv would've solved most of his issues too. But I agree with him in that Python documentation could be better. Or have a more unified system in place. I feel like every other how to doc I read on setting something Python up uses a different environment containment product.

by sysworld

3/20/2026 at 2:35:33 AM

Conda was fantastic up to some point last year and since then I've had quite a few unresolvable version issues with it. It is really annoying, especially when you're tying multiple things together and each requires its own set of mutually exclusive specific versions of libraries. The latest like that was gnu radio and some out-of-tree stuff at the same time as a bluetooth library. High drama. I eventually gave up, rewrote the whole thing in a different language and it took less time than I had spent on trying to get the python solution duct-taped together.

I should learn to give up quicker.

by jacquesm

3/20/2026 at 1:46:22 AM

Because I need a new version of python very rarely (years go by). I don't remember all the arcane incantations to set everything up.

I did eventually do that though, and I'm pretty sure I had to mess about with installing and uninstalling torch.

I dread using anything made in python because of this. It's always annoying and never just works (if the version of python is incompatible, otherwise it's fine) .

by Aerroon

3/20/2026 at 9:34:21 AM

I don't know, I'm pretty happy with Conda. I just create a new environment and install on it. It normally works.

Even if you have to install using pip it just affect the active environment.

Maybe I'm only trying simple things.

by RobertoG

3/20/2026 at 3:57:20 AM

damnn, really sorry for the inconv, looks like some folks are having bad env issues. we're working on fixing this.

by rohan_joshi

3/20/2026 at 4:43:25 PM

It's absolutely not your fault. It's a skill issue and compatibility issue on my end and/or python. You guys are doing amazing.

by Aerroon

3/20/2026 at 3:33:36 AM

Two words; Nix Flakes

by Teknomadix

3/20/2026 at 5:35:14 PM

To the folks and Kitten team: I'm working on TTS as a problem statement (for an application), and what is the best model at the latency/cost inference. I'm currently settling for gemini TTS, which allows for a lot of expressiveness, but a word at 150ms starts to hurt when the content is a few sentences.

my current best approach is wrapping around gemini-flash native, and the model speaking the text i send it, which allows me end to end latency under a second.

are there other models at this or better pricing i can be looking at.

by anilgulecha

3/19/2026 at 10:29:48 PM

Was playing around a bit and for its size it's very impressive. Just has issues pronounciating numbers. I tried to let it generate "Startup finished in 135 ms."

I didn't expect it to pronounciate 'ms' correctly, but the number sounded just like noise. Eventually I got an acceptable result for the string "Startup finished in one hundred and thirty five seconds.

by __fst__

3/19/2026 at 10:42:00 PM

yeah we're fixing this at the model level too. but in the meantime, there is a way to add text preprocessing for you, and if you have a special use-cased, claude code should be able to one-shot custom preprocessing. its the way that most existing tts models (including sota cloud ones) deal w numbers and units, they just convert it into string.

by rohan_joshi

3/19/2026 at 10:43:16 PM

thanks a lot for trying it and giving feedback. custom preprocessing will fix this for 95% of use-cases. and as i mentioned, this will be fixed at the model level in the next release.

by rohan_joshi

3/19/2026 at 11:26:46 PM

I tried it with some "hard mode" text:

The above SECDED check-bit encoding can be implemented in a similar way, but since it uses only three-bit patterns, mapping syndromes to correction masks can be done with three-input AND gates.

It sounded quite good indeed for the normal English stuff, but I guess predictably was quite bad at the domain-specific words. It misspoke "SECDED", had wrong emphasis on "syndromes", and pronounced "AND gates" like "and gates".

Could you give some example of what kind of preprocessing would help in this case? I tried some local LLMs, but they didn't do a good job (maybe my prompts sucked).

by magicalhippo

3/19/2026 at 11:23:13 PM

> pronounciating

I'm not sure if you're misspelling it deliberately or not, but the word you're looking for is "pronounce" and it's verb form "pronouncing", as in "It just has issues pronouncing numbers" and "I didn't expect it to pronounce 'ms' correctly."

by nozzlegear

3/20/2026 at 6:56:52 AM

Very cool :) Look forward to trying it out

Maybe a dumb and slightly tangential question, (I don't mean this as a criticism!) but why not release a command line executable?

Even the API looks like what you'd see in a manpage.

I get it wouldn't be too much work for a user to actually make something like that, I'm just curious what the thought process is

by geokon

3/20/2026 at 7:04:08 AM

great idea, we'll do that too. we just decided to launch an onnx first and get some feedback. we'll be simplifying the process of running it everywhere including a command line executable.

by rohan_joshi

3/19/2026 at 8:12:42 PM

A very clear improvement from the first set of models you released some time ago. I'm really impressed. Thanks for sharing it all.

by daneel_w

3/19/2026 at 8:17:18 PM

thanks a lot. yeah these models are way better than our previous launch. our 15M model now is better than our previous 80M model and we expect to continue seeing this rate of improvement.

by rohan_joshi

3/20/2026 at 8:11:39 AM

The size/quality tradeoff here is interesting. 25MB for a TTS model that's usable is a real achievement, but the practical bottleneck for most edge deployments isn't model size -- it's the inference latency on low-power hardware and the audio streaming architecture around it. Curious how this performs on something like a Raspberry Pi 4 for real-time synthesis. The voice quality tradeoff at that size usually shows up most in prosody and sentence-final intonation rather than phoneme accuracy.

by bobokaytop

3/20/2026 at 2:36:27 AM

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.

by jacquesm

3/20/2026 at 4:02:12 AM

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

by rohan_joshi

3/19/2026 at 11:49:36 PM

I'd love to see a monolingual Japanese model sometime in the future. Qwen3-tts works for Japanese in general, but from time to time it will mix with some Mandarin in between, making it unusable.

by _hzw

3/20/2026 at 1:43:35 AM

You could try a preprocessing step where you convert to hiragana, but I guess that would lose pitch accent information (e.g. 飴 vs 雨)

by meatmanek

3/20/2026 at 2:20:25 AM

Exactly. Qwen only has one pitch accent for pure hiragana words, even though it actually work (removing mandarin mixed-in), which requires some great efforts to normalize text in order to disambiguate heteronyms, the result is (if you use voice cloning) your favorite CV speaking in some weird, unknown accent :)

by _hzw

3/20/2026 at 3:46:01 AM

our next model(eta 3ish weeks) will support Japanese. would love to get your feedback then on how the quality is. can you share what usecase you want? would love to support it.

by rohan_joshi

3/20/2026 at 4:42:42 PM

I have a pipeline of jp epub>m4b, just need to swap tts models in between :)

by _hzw

3/19/2026 at 4:46:56 PM

You should put examples comparing the 4 models you released - same text spoken by each.

by ks2048

3/19/2026 at 10:37:11 PM

I ran install instructions and it took 7.1GB of deps, tf you mean "tiny" ?

by PunchyHamster

3/19/2026 at 10:39:27 PM

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.

by rohan_joshi

3/19/2026 at 11:02:22 PM

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 down to ~3 GiB (& about 1.3 GiB if you wipe your uv cache afterwards) on Linux if I add the following to the end of `pyproject.toml`:

  [tool.uv.sources]
  # This tells uv to use the specific index for torch, torchvision, and torchaudio
  torch = [
      {index = "pytorch-cpu"}
  ]
  torchvision = [
      {index = "pytorch-cpu"}
  ]
  torchaudio = [
      {index = "pytorch-cpu"}
  ]
  
  [[tool.uv.index]]
  name = "pytorch-cpu"
  url = "https://download.pytorch.org/whl/cpu"
& add "torch" to the direct dependencies, b/c otherwise it seems like uv is ignoring the source? (… which of course downloads a CPU-only torch.)

This is an example of what one sees under Linux:

  nvidia-nvjitlink-cu12      ------------------------------ 23.83 MiB/37.44 MiB
  nvidia-curand-cu12         ------------------------------ 23.79 MiB/60.67 MiB
  nvidia-cuda-nvrtc-cu12     ------------------------------ 23.87 MiB/83.96 MiB
  nvidia-nvshmem-cu12        ------------------------------ 23.62 MiB/132.66 MiB
  triton                     ------------------------------ 23.82 MiB/179.55 MiB
  nvidia-cufft-cu12          ------------------------------ 23.76 MiB/184.17 MiB
  nvidia-cusolver-cu12       ------------------------------ 23.84 MiB/255.11 MiB
  nvidia-cusparselt-cu12     ------------------------------ 23.99 MiB/273.89 MiB
  nvidia-cusparse-cu12       ------------------------------ 23.96 MiB/274.86 MiB
  nvidia-nccl-cu12           ------------------------------ 23.79 MiB/307.42 MiB
  nvidia-cublas-cu12         ------------------------------ 23.73 MiB/566.81 MiB
  nvidia-cudnn-cu12          ------------------------------ 23.56 MiB/674.02 MiB
  torch                      ------------------------------ 23.75 MiB/873.22 MiB
That's not all the libraries, either, but you can see NVIDIA here is easily over 1 GiB.

It also then crashes for me, with:

  File "KittenTTS/.venv/lib/python3.14/site-packages/pydantic/v1/fields.py", line 576, in _set_default_and_type
    raise errors_.ConfigError(f'unable to infer type for attribute "{self.name}"')
  pydantic.v1.errors.ConfigError: unable to infer type for attribute "REGEX"
Which seems to be [this bug in spacey](https://github.com/explosion/spaCy/issues/13895), so I'm going to have to try adding `<3.14` to `requires-python` in `pyproject.toml` too I think. That is, for anyone wanting to try this out:

  -requires-python = ">=3.8"
  +requires-python = ">=3.8,<3.14"
(This isn't really something KittenTTS should have to do, since this is a bug in spacey … and ideally, at some point, spacey will fix it.)

Also:

  + curated-tokenizers==0.0.9
This version is so utterly ancient that there aren't wheels for it anymore, so that means a loooong wait while this builds. It's pulled in via misaki, and my editor says your one import of misaki is unused.

Hilariously, removing it breaks but only on macOS machine. I think you're using it solely for the side-effect that it tweaks phonemizer to use espeakng, but you can just do that tweak yourself, & then I think that dependency can be dropped. That drops a good number of dependencies & really speeds up the installation since we're not compiling a bunch of stuff.

You need to add `phonemizer-fork` to your dependencies. (If you remove misaki, you'll find this missing.)

by deathanatos

3/20/2026 at 4:08:55 AM

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

by rohan_joshi

3/20/2026 at 2:52:20 AM

a classic "how to draw an owl" lol :)

by zeroq

3/19/2026 at 8:47:10 PM

They sound like cartoon voices... but I really like them I could listen to a book with those.

by nsnzjznzbx

3/19/2026 at 9:03:46 PM

yeah we tried to include those voices in this release to showcase the expressivity. but we've already started adding more professional sounding voices for prod use-cases.

by rohan_joshi

3/20/2026 at 10:42:57 AM

Yeah, I was wondering if it's all helium voices. Should maybe try and see or find more demos.

by a96

3/20/2026 at 3:00:59 PM

Nice, but it's weird that no "language" or "English" is mentioned on the github page, and only from the "Release multilingual TTS" Roadmap item could I guess it's probably English only for now.

by spyder

3/19/2026 at 4:39:43 PM

One of the core features I look for is expressive control.

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?

by altruios

3/19/2026 at 5:02:33 PM

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

by rohan_joshi

3/19/2026 at 5:42:37 PM

Emotion based tagging control would be the most helpful narrowing it down. Tags like [sarcastically] [happily] [joyfully] [fearfully]: so a subsection of adverbs.

A stretch goal is 'arbitrary tags' from [singing] [sung to the tune of {x}] [pausing for emphasis] [slowly decreasing speed for emphasis] [emphasizing the object of this sentence] [clapping] [car crash in the distance] [laser's pew pew].

But yeah: instruction/control via [tags] is the deciding feature for me, provided prompt adherence is strong enough.

Also: a thought...

Everyone is using [] for different kinds of tags in this space: which is very simple. Maybe it makes sense to differentiate kinds of tags? I.E. [tags for modifying how text is spoken] vs {tags for creating sounds not specifically speech: not modifying anything... but instead it's own 'sound/word'}

by altruios

3/19/2026 at 6:20:31 PM

yeah i think to start with, narrowing it down to a few tags would be most helpful and we'll probably start w that first. Thanks a lot!

by rohan_joshi

3/19/2026 at 8:17:52 PM

Intonation (frequency rise/fall) would offer a lot of versatility.

by daneel_w

3/20/2026 at 2:55:42 AM

not OP but something like [<intention>] where intention might be something like anger, curiousness, etc. [long pause], [gasp], [laughter] stuff like that.

by zeroq

3/19/2026 at 11:56:15 PM

The Github readme doesn't list this: what data trained this? Was it done by the voices of the creators, or was this trained on data scraped from the internet or other archives?

by jamamp

3/19/2026 at 11:18:00 PM

Fingers crossed for a normal-sounding voice this time around. The cute Kitten voices are nice, but I want something I can take seriously when I'm listening to an audiobook.

by arcanemachiner

3/19/2026 at 11:31:53 PM

How is the Bruno voice for this one? there will also be another release in ~15-20 days where we have more professional voices. if you'd like to get early access and give feedback lmk, or dm me.

by rohan_joshi

3/19/2026 at 11:40:39 PM

Hey Rohan, love to contribute feedback.

Huge fan of Ava multilingual and hopefully there are many other others with similar taste, so my feedback might shape things towards a halfway decent direction at least for some.

btw, use case is most often to listen to news/articles.

by Barbing

3/20/2026 at 6:46:33 AM

got it, this is very useful. thanks a lot.

by rohan_joshi

3/20/2026 at 12:42:19 AM

Not too bad, actually! Looking forward to hearing some more voices.

No need to DM me, just post on HN or /r/LocalLLama and I'll catch wind of it.

Thanks for your work!

by arcanemachiner

3/19/2026 at 8:12:55 PM

Great stuff. Is your team interested in the STT problem?

by boutell

3/19/2026 at 8:18:16 PM

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?

by rohan_joshi

3/19/2026 at 11:48:24 PM

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.

[ps-not parent commenter]

by Barbing

3/20/2026 at 3:09:54 AM

Thank you for this link.

by _boffin_

3/20/2026 at 4:09:23 AM

got it, this helps a lot. thanks!

by rohan_joshi

3/19/2026 at 10:35:39 PM

From my point of view, Parakeet is not very good at formatting the output, so it would be nice if a small model focused on having nicely formatted (and correct) text, not just the lowest WER score. Rewarding the model for inserting logical line breaks, quotation marks, etc.

by coder543

3/19/2026 at 10:11:31 PM

Home Assistant integration a la Alexa would be awesome

by bavell

3/19/2026 at 4:52:40 PM

There's a number of recent, good quality, small TTS models.

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.

by ks2048

3/19/2026 at 4:57:33 PM

Any recommendations?

by the_duke

3/19/2026 at 7:27:56 PM

Depends how small or complex you want a TTS, as flite + flitevox voice packages worked on pi or zynq ARM cpu just fine. =3

Also:

https://github.com/sparkaudio/spark-tts

by Joel_Mckay

3/19/2026 at 4:54:09 PM

[flagged]

by okokwhatever

3/20/2026 at 2:38:47 AM

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

by swaminarayan

3/20/2026 at 4:14:55 AM

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.

by rohan_joshi

3/19/2026 at 6:42:04 PM

This is awesome, well done. Been doing lot of work with voice assistants, if you can replicate voice cloning Qwen3-TTS into this small factor, you will be absolute legends!

by armcat

3/19/2026 at 6:51:21 PM

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

by rohan_joshi

3/19/2026 at 8:01:48 PM

That's sick, looking forward to it! You have my email in the profile, please let me know when you do!

by armcat

3/20/2026 at 11:06:13 AM

the dependency chain issue is a real barrier for edge deployment. i've been running tts models on a raspberry pi for a home automation project and anything that pulls torch + cuda makes the whole thing a non-starter. 25MB is genuinely exciting for that use case.

curious about the latency characteristics though. 1.5x realtime on a 9700 is fine for batch processing but for interactive use you need first-chunk latency under 200ms or the conversation feels broken. does anyone know if it supports streaming output or is it full-utterance only?

the phoneme-based approach should help with pronunciation consistency too. the models i've tried that work on raw text tend to mispronounce technical terms unpredictably — same word pronounced differently across runs.

by baibai008989

3/20/2026 at 2:00:53 PM

Could you share what you're currently using?

by oybng

3/19/2026 at 6:39:39 PM

The example.py file says "it will run blazing fast on any GPU. But this example will run on CPU."

I couldn't locate how to run it on a GPU anywhere in the repo.

by pumanoir

3/19/2026 at 6:52:01 PM

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

by rohan_joshi

3/20/2026 at 1:38:56 AM

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

by stbtrax

3/20/2026 at 4:12:45 AM

i can confirm that we did not.

by rohan_joshi

3/20/2026 at 4:19:10 AM

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.

by stbtrax

3/19/2026 at 5:31:19 PM

A lot of good small TTS models in recent times. Most seem to struggle hard on prosody though.

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?

by magicalhippo

3/19/2026 at 6:13:59 PM

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.

by rohan_joshi

3/19/2026 at 10:14:02 PM

Listened to the video examples, sounded very good though wasn't terribly challenging text.

If only I could have that in Norwegian my SO would be pleased.

Also I totally misremembered regarding Kokoro TTS. It's good, but not what was butchering Norwegian. Forgot which one I was thinking of, maybe it was the old VITS stuff Rhaspy uses. Points stand, the voice was good but could barely understand what was said.

by magicalhippo

3/19/2026 at 5:46:22 PM

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

by soco

3/19/2026 at 6:18:07 PM

yes. the current release of our model is english-only. so other languages are not expected to perform well. we'll try to look out for this in our multilingual release.

by rohan_joshi

3/19/2026 at 5:38:40 PM

A lot of these models struggle with small text strings, like "next button" that screen readers are going to speak a lot.

by devinprater

3/19/2026 at 5:45:04 PM

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?

by soco

3/19/2026 at 6:22:21 PM

we'd love to serve this use-case. i'll make a demo for this next week and comment here with it.

by rohan_joshi

3/19/2026 at 4:51:00 PM

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.

by fwsgonzo

3/19/2026 at 4:57:18 PM

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.

by rohan_joshi

3/20/2026 at 4:44:08 AM

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

by koolala

3/19/2026 at 7:34:57 PM

desktop CPUs running inference on a single background thread would be the ideal case for what I'm considering.

by fwsgonzo

3/19/2026 at 6:52:58 PM

Would an Android app of this be able to replace the built in tts?

by vezycash

3/19/2026 at 6:54:44 PM

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?

by rohan_joshi

3/19/2026 at 6:59:56 PM

I use an epub reader like Moon+ with the built in TTS to turn epubs into audiobooks, and I tried Kokoro TTS but the issue was too much lag between sentences plus it doesn't preprocess the next sentence while it reads out the current one.

by satvikpendem

3/19/2026 at 7:06:04 PM

okay this seems pretty doable, i think i know someone who is working on an epub reader using kittentts. if they don't post about it, i'll do it once its done.

by rohan_joshi

3/19/2026 at 7:09:42 PM

Working on a reader and server that use pockettts to turn epubs into audio books https://github.com/gabrielcsapo/compendus shows a virtual scroller for the text and audio

by gabrielcsapo

3/20/2026 at 2:44:49 AM

I thought they were going to make kitten sounds instead of speech

by agnishom

3/20/2026 at 4:15:34 AM

for that, a 100KB model could be enough ;)

by rohan_joshi

3/20/2026 at 2:52:52 AM

I guess they are Discord kittens?

by casey2

3/20/2026 at 7:01:27 AM

Only American voices? For some reason I'm only interested in Irish, British or Welsh accents. American is a no

by tim-projects

3/20/2026 at 8:13:14 AM

minor nit to pick: Welsh accents are British accents as Wales is in Britain. In fact by some definitions it's the most British part.

People from outside the UK often use British as synonymous with English, and in the context of accents, often a South East English accent or some sort of Received Pronunciation (RP) accent. Technically a "British" accent could be from anywhere in England, Scotland, or Wales, and therefore by extension might not even be the English language.

While I'm here, since it's generally confusing, the UK is Great Britain and Northern Ireland. Great Britain is England, Scotland, and Wales.

by foo42

3/20/2026 at 2:02:28 PM

I am actually English but I'm so used to speaking with international people I instinctively say British instead of English - because that's what people expect.

So being factually correct doesn't really matter. Nobody cares and nobody wants to learn so I adapt for them.

In the same way I almost exclusively write with American spelling now. Life is just easier when you stop fighting.

by tim-projects

3/20/2026 at 7:43:32 AM

Found they struggle with numbers. Like, give them a random four digit number in a sentence and it fumbles.

by Stevvo

3/20/2026 at 5:48:25 AM

Is this open-source or open-weights ML?

by pabs3

3/20/2026 at 6:44:57 AM

yes, indeed. we are working on adding mit licensed phonemizers too by this weekend, so you'll be able to use these models as you like :)

by rohan_joshi

3/19/2026 at 4:35:40 PM

Thanks for open sourcing this.

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.

by ilaksh

3/19/2026 at 4:46:44 PM

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.

by rohan_joshi

3/19/2026 at 6:40:34 PM

Right now it's outgoing calls for a small business client that checks information. Although if they call back they don't mind an automated system, on outgoing calls the person answering will often hang up if they detect AI right away, so we use a realistic custom voice with an accent.

This is a mind numbing task that requires workers to make hundreds of calls each day with only minor variations, sometimes navigating phone trees, half the time leaving almost the exact same message.

Anyway, I believe almost all such businesses will be automated within months. Human labour just cannot compete on cost.

by ilaksh

3/20/2026 at 4:35:03 PM

I don't like the sound of that. Why do humans always need to spoil new advancements by finding the worst use cases?

by RobMurray

3/19/2026 at 9:40:53 PM

How long until I can buy this as a chip for my Arduino projects?

by amelius

3/19/2026 at 10:44:32 PM

not v long. until then you start running tts on phones, wearables and r pis. at the model level, we'll have a model for this kind of mcu's later this year.

by rohan_joshi

3/20/2026 at 12:26:17 AM

You can (just about?) already run on a pi zero, right? That's not literally a chip, but in practical utility it can't be very different

by yjftsjthsd-h

3/20/2026 at 11:18:25 AM

A CPU will probably consume much more power.

by amelius

3/19/2026 at 5:48:09 PM

This would be great as a js package - 25mb is small enough that I think it'd be worth it (in-browser tts is still pretty bad and varies by browser)

by DavidTompkins

3/19/2026 at 6:19:04 PM

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

by rohan_joshi

3/19/2026 at 4:33:34 PM

Thanks for working on this!

Is 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.

by great_psy

3/19/2026 at 4:49:50 PM

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!

by rohan_joshi

3/20/2026 at 9:41:18 AM

How noticeable is the difference in quality between the 4M model and the 80M model?

by erkoo

3/20/2026 at 7:33:14 AM

The <25MB figure is what stands out. Been wanting to add TTS to a few Next.js projects for offline/edge scenarios but model sizes have always made it impractical to ship.

At 25MB you can actually bundle it with the app. Going to test whether this works in a Vercel Edge Function context -- if latency is acceptable there it opens up a lot of use cases that currently require a round-trip to a hosted API.

by rsmtjohn

3/19/2026 at 6:19:08 PM

I'm still looking for the "perfect" setup in order to clone my voice and use it locally to send voice replies in telegram via openclaw. Does anyone have auch a setup?

I want to be my own personal assistant...

EDIT: I can provide it a RTX 3080ti.

by sschueller

3/19/2026 at 6:48:02 PM

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.

by ilaksh

3/19/2026 at 7:52:05 PM

Try training a model on piper, you will need to record a lot of utterances but the results are pretty great and the output is a fast TTS model.

by nicpottier

3/19/2026 at 6:22:24 PM

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

by justanotherunit

3/19/2026 at 9:26:18 PM

Why not just send text replies? You can already do that

by bdbdbdb

3/19/2026 at 6:33:39 PM

Really cool to see innovation in terms of quality of tiny models. Great work!

by schopra909

3/19/2026 at 6:53:46 PM

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

by rohan_joshi

3/19/2026 at 7:06:37 PM

are there plans to output text alignment?

by gabrielcsapo

3/19/2026 at 7:07:43 PM

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

by rohan_joshi

3/19/2026 at 7:15:46 PM

that would be awesome, I was using pockettts then I had to run it through whisper to get the accurate alignment. Not super productive for realtime work.

by gabrielcsapo

3/19/2026 at 6:41:02 PM

What's the actual install size for a working example? Like similar "tiny" projects, do these models actually require installing 1GB+ of dependencies?

by janice1999

3/19/2026 at 7:12:54 PM

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.)

So I toyed with this a bit + the Rust library "ort", and ort is only 224M in release (non-debug) mode, and it was pretty simple to run this model with it. (I did not know ort before just now.) I didn't replicate the preprocessing the Python does before running the model, though. (You have to turn the text into an array of floats, essentially; the library is doing text -> phonemes -> tokens; the latter step is straight-forward.)

by deathanatos

3/19/2026 at 10:41:05 PM

So, that was on macOS. It's actually huge on Linux, and I've run out of disk space trying to pull dependencies. It's nvidia, who always shows great judgement in their use of disk.

by deathanatos

3/19/2026 at 7:21:01 PM

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

by wedowhatwedo

3/19/2026 at 5:31:07 PM

I'm thinking of giving "voice" to my virtual pets (think Pokemon but less than a dozen). The pets are made up animals but based on real animal, like Mouseier from Mouse (something like that). Is this possible?

Tldr: generate human-like voice based on animal sound. Anyway maybe it doesn't make sense.

by wiradikusuma

3/19/2026 at 6:57:58 PM

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.

by rohan_joshi

3/19/2026 at 4:36:40 PM

Is it English only?

by Tacite

3/19/2026 at 4:51:46 PM

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.

by rohan_joshi

3/19/2026 at 7:49:49 PM

Spanish would be great, there's a serious lack of Spanish TTS on Android compared to iOS and the quality is not the best.

by ivm

3/19/2026 at 10:46:05 PM

spanish model will be out in a matter of weeks.

by rohan_joshi

3/20/2026 at 4:46:03 PM

Great, thanks

by jorgejiro

3/20/2026 at 7:09:12 AM

Here to suggest the Bengali language! It has the 7th largest speaker base worldwide but often ignored by tech companies, sadly.

by hattimaTim

3/19/2026 at 6:54:43 PM

French, Spanish, German would go a long way.

by Zopieux

3/19/2026 at 10:46:56 PM

french, spanish and german models will also be out v soon. these are languages we are working on already. some lower resource languages will take longer.

by rohan_joshi

3/19/2026 at 6:59:20 PM

This is great. Demo looks awesome.

by whitepaper27

3/19/2026 at 7:06:35 PM

thanks, glad you liked it

by rohan_joshi

3/20/2026 at 5:46:11 AM

Whats the training data for this?

by pabs3

3/20/2026 at 5:52:05 AM

Sounds like the voice actors from Critical Role but I just came off of watching 48 hours of Campaign 3 so I'm probably imagining things.

by phyzix5761

3/20/2026 at 1:37:12 AM

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, since from there it should just be invoking the model.

edit: it really helps to use the same model facepalm. It's the 80M model, and it happens on both OS. Wildly the nano gets it better? I'm going to join the Discord lol.

by deathanatos

3/20/2026 at 4:17:03 AM

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.

by rohan_joshi

3/19/2026 at 8:36:49 PM

sounds amazing! does it stream? or is it so fast you don't need to?

by exe34

3/19/2026 at 10:30:06 PM

it can support chunk streaming, i'm working on adding it to the repo. should be up by tomorrow.

by rohan_joshi

3/19/2026 at 8:52:11 PM

Wow, what an amazing feat. Congratulations!

by moralestapia

3/19/2026 at 10:30:18 PM

thank you so much. glad you liked the model.

by rohan_joshi

3/19/2026 at 11:33:27 PM

This is something I've been looking for (the <50MB models in particular). Unfortunately my feedback is as follows:

      Downloading https://github.com/KittenML/KittenTTS/releases/download/0.8.1/kittentts-0.8.1-py3-none-any.whl (22 kB)
    Collecting num2words (from kittentts==0.8.1)
      Using cached num2words-0.5.14-py3-none-any.whl.metadata (13 kB)
    Collecting spacy (from kittentts==0.8.1)
      Using cached spacy-3.8.11-cp314-cp314-win_amd64.whl.metadata (28 kB)
    Collecting espeakng_loader (from kittentts==0.8.1)
      Using cached espeakng_loader-0.2.4-py3-none-win_amd64.whl.metadata (1.3 kB)
    INFO: pip is looking at multiple versions of kittentts to determine which version is compatible with other requirements. This could take a while.
    ERROR: Ignored the following versions that require a different python version: 0.7.10 Requires-Python >=3.8,<3.13; 0.7.11 Requires-Python >=3.8,<3.13; 0.7.12 Requires-Python >=3.8,<3.13; 0.7.13 Requires-Python >=3.8,<3.13; 0.7.14 Requires-Python >=3.8,<3.13; 0.7.15 Requires-Python >=3.8,<3.13; 0.7.16 Requires-Python >=3.8,<3.13; 0.7.17 Requires-Python >=3.8,<3.13; 0.7.5 Requires-Python >=3.8,<3.13; 0.7.6 Requires-Python >=3.8,<3.13; 0.7.7 Requires-Python >=3.8,<3.13; 0.7.8 Requires-Python >=3.8,<3.13; 0.7.9 Requires-Python >=3.8,<3.13; 0.8.0 Requires-Python >=3.8,<3.13; 0.8.1 Requires-Python >=3.8,<3.13; 0.8.2 Requires-Python >=3.8,<3.13; 0.8.3 Requires-Python >=3.8,<3.13; 0.8.4 Requires-Python >=3.8,<3.13; 0.9.0 Requires-Python >=3.8,<3.13; 0.9.2 Requires-Python >=3.8,<3.13; 0.9.3 Requires-Python >=3.8,<3.13; 0.9.4 Requires-Python >=3.8,<3.13; 3.8.3 Requires-Python >=3.9,<3.13; 3.8.5 Requires-Python >=3.9,<3.13; 3.8.6 Requires-Python >=3.9,<3.13; 3.8.7 Requires-Python >=3.9,<3.14; 3.8.8 Requires-Python >=3.9,<3.14; 3.8.9 Requires-Python >=3.9,<3.14
    ERROR: Could not find a version that satisfies the requirement misaki>=0.9.4 (from kittentts) (from versions: 0.1.0, 0.3.0, 0.3.5, 0.3.9, 0.4.0, 0.4.4, 0.4.5, 0.4.6, 0.4.7, 0.4.8, 0.4.9, 0.5.0, 0.5.1, 0.5.2, 0.5.3, 0.5.4, 0.5.5, 0.5.6, 0.5.7, 0.5.8, 0.5.9, 0.6.0, 0.6.1, 0.6.2, 0.6.3, 0.6.4, 0.6.5, 0.6.6, 0.6.7, 0.7.0, 0.7.1, 0.7.2, 0.7.3, 0.7.4)
    ERROR: No matching distribution found for misaki>=0.9.4
I realize that I can run a multiple versions of python on my system, and use venv to managed them (or whatever equivalent is now trendy), but as I near retirement age all those deep dependencies nets required by modern software is really depressing me. Have you ever tried to build a node app that hasn't been updated in 18 months? It can't be done. Old man yelling at cloud I guess shrugs.

by tredre3

3/19/2026 at 11:37:27 PM

this is some env issue sorry for the inconvenience, lemme fix it. can you dm me w your env? discord / github / mail / anywhere works.

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3/20/2026 at 3:05:55 PM

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by eddie-wang

3/19/2026 at 5:49:36 PM

25MB is impressive. What's the tradeoff vs the 80M model — is it mainly voice quality or does it also affect pronunciation accuracy on less common words?

by Remi_Etien

3/19/2026 at 6:16:46 PM

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.

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