JSLT VS bark

I follow that approach in this open-source repo, and since PRs come from volunteers I've sometimes just updated the docs afterwards myself. But in a work situation you could be strict about it.

I made this language. It was a lot of fun, and has been very useful.

If you're working in Java I would look at JSLT for the JSON transforms. (Disclaimer: I created JSLT, for a similar use case.)

You could use a transformation language like JSLT to write a transform, then apply it to all files. Not sure if that's suitable for you.

To my knowledge, the model being used for this is "chirp" which is 'based on' bark[1], an AI text to speech model.

The github page for bark links to a page about chirp, which returns a 404 page for me [2]. that the model for suno.ai's song generator isn't too much different than the text to speech model.

My hunch is that it was something like a coincidence that the bark model was capable of producing music, and that was spun off into this product. Unfortunately, there seems to still be issues with bark when generating long (like book length) spoken audio. Which is too bad, as someone who's worked jobs that require lots of driving, it would be awesome to be able to have any text read to me in a natural sounding voice.

[1]https://github.com/suno-ai/bark

Stable-audio and MusicGen sounds better than Jukebox.

But the best so far is Suno.ai ( https://app.suno.ai ) especially with their V3 model they have very impressive results, the fidelity is not studio quality but they're getting very close.

It's very likely based on their TTS model they have released before Bark, but trained on more data and with higher resolution.

https://github.com/suno-ai/bark

https://github.com/suno-ai/bark

> Bark was developed for research purposes. It is not a conventional text-to-speech model but instead a fully generative text-to-audio model, which can deviate in unexpected ways from provided prompts. Suno does not take responsibility for any output generated. Use at your own risk, and please act responsibly.

I've generated probably >200 songs now with Suno, of which perhaps 10 have been any good, and I can't detect any pattern in terms of the outputs.

Here's another one which is pretty good. I accidentally copied and pasted the prompt and lyrics, and it's amazing to me how 'musically' it renders the prompt:

hahah wow! cool :-)

PS: OT, I am reading this Bark thing(https://github.com/suno-ai/bark). Can I run it locally on a Macbook 2015 with 8GB RAM?

I have it locally. The model is on huggingface. It runs with about 8GB VRAM.

suno-ai/bark

In contrast, Tortoise excels at cloning voices using just short audio samples. Its autoencoder compression enables efficiently capturing speaker characteristics. As explained in the source code repo for Suno's implementation, users can clone voices by providing a few audio clips of a target speaker.