211–220 of 383 posts
Reddit post with generated audio sample: https://www.reddit.com/r/LocalLLaMA/comments/1mhyzp7/kitten_...
The reddit video is awesome. I don't understand how people are calling it an OK model. Under 25MB and cpu only for this quality is amazing.
I'm curious why smallish TTS models have metallic voice quality. The pronunciation sounds about right - i thought it's the hard part. And the model does it well. But voice timbre should be simpler to fix? Like, a simple FIR might improve it?
I tried it. Not bad for the size (of the model) and speed. Once you install all the massive number of libraries and things needed we are a far cry away from 25MB though. Cool project nonetheless.
It mentions ONNX, so I imagine an ONNX model is or will be available. ONNX runtime is a single library, with C#'s package being ~115MB compressed. Not tiny, but usually only a few lines to actually run and only a single dependency.
Which is completely reasonable imho, but obviously comes with tradeoffs.
Earlier quoted context omitted.
Okay, what's stopping you from feeding the code into an LLM and re-write it and make it yours? You can even add extra steps like make it analyze the code block by block then supervise it as it is rewriting it. Bam. AI age IP freedom. Morals may stop you but other than that? IMHO all open source code is public domain code if anyone is willing to spend some AI tokens.
Tell me you haven't used LLMs on large, non-trivial codebases without telling me... :)
You don't give the whole codebase to an LLM and expect it to have one shot output. Instead, you break it down and and write the code block by block. Then the size if the codebase doesn't matter. You use the LLM as a tool, it is not supposed to replace you. You don't try to become George from Jetsons who is just pressing a button and doesn't touch anything, instead you are on top of it as the LLM does the coding. You test the code on every step to see if the implementation behaves as expected. Do enough of this and you have proper, full "bespoke" software.
System Requirements Works literally everywhere Haha, on one of my machines my python version is too old, and the package/dependencies don't want to install. On another machie the python version is too new, and the package/dependencies don't want to install.
Such an ignorant thing to say for something that requires 25MB RAM.
I send you a 500kb Windows .exe file and claim it runs literally everywhere.
Would it be ignorant to say anything against it because of its size?
Microsoft's and some of Google's TTS models make the simplest mistakes. For instance, they sometimes read "i.e." as "for example." This is a problem if you have low vision and use TTS for, say, proofreading your emails. Why does it happen? I'm genuinely curious.
Well, speech synthesizers are pretty much famous for speaking all sorts of things wrong. But what I find very concerning about LLM based TTS is that some of them cant really speak numbers greater then 100. They try, but fail a lot. At least tts-1-hd was pretty much doing this for almost every 3 or 4 digit number. Especially noticeable when it is supposed to read a year number.
Looks like they are sidestepping these kinds of issues by generating the phonemes with the preprocessing stage of traditional speech synthesizers, and using the LLM only to turn those phonemes into natural-ish sounding speech. That limits how natural the model can become, but it should be able to correctly pronounce anything the preprocessing can pronounce
I tried it. Not bad for the size (of the model) and speed. Once you install all the massive number of libraries and things needed we are a far cry away from 25MB though. Cool project nonetheless.
Usually pulling in lots of libraries helps develop/iterate faster. Then can be removed later once the whole thing starts to take shape.
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…
> It’s that KittenTTS is Apache-2.0 Have you seen the code[1] in the repo? It uses phonemizer[2] which is GPL-3.0 licensed. In its current state, it's effectively GPL licensed. [1]: https://github.com/KittenML/KittenTTS/blob/main/kittentts/on... [2]: https://github.com/bootphon/phonemizer Edit: It looks like I replied to an LLM generated comment.
If my MIT-licensed one-line Python library has this line of code…
run([“bash”, “-c”, “echo hello”])
(But, to argue against my own point, if an OS vendor ships my library alongside a copy of bash, do they have to now relicense my library as GPL?)
Earlier quoted context omitted.
Does anybody find it funny that sci-fi movies have to heavily distort "robot voices" to make them sound "convincingly robotic"? A robotic, explicitly non-natural voice would be perfectly acceptable, and even desirable, in many situations. I don't expect a smart toaster to talk like a BBC host; it'd be enough is the speech if easy to recognize.
This one is at least an interesting idea: https://genderlessvoice.com/
It’s a good choice for a robot voice. It’s easier to understand than the formant synths or deliberately distorted human voices. The genderless aspect is alien enough to avoid the uncanny valley. You intuitively know you’re dealing with something a little different.