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README.md

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-# Kokoro
+# kokoro
 
-This repository is a work in progress. If you know, you know!
+This WIP repository is intended to be an inference library for https://hf.co/hexgrad/Kokoro-82M
 
-If you don't: https://hf.co/hexgrad/Kokoro-82M
+It is under construction and likely will not be useful until the [next base model release](https://huggingface.co/hexgrad/Kokoro-82M/discussions/36).
+
+The goal is to be able to `pip install kokoro` and offer some of the design goals and functionalities laid out below.
+
+### G2P will be imported from Misaki
+[Misaki](https://github.com/hexgrad/misaki) is a G2P engine with language-specific solutions:
+```sh
+pip install misaki[en] # installs English
+pip install misaki[ja] # installs Japanese
+```
+Users who don't peek under the hood may not care, since `import kokoro` will simply `import misaki` and life goes on. This is likely the proper separation of responsibilities, and not all users will want or need all languages.
+
+### Smarter LF chunking
+Kokoro models have a 512 token context window, which usually amounts to about 30 seconds of audio. Finding natural stopping points in your text to chop is key to smooth long-form (LF) generation, which should be much easier with token-level traces in `misaki[en]` (hopefully other languages to follow).
+
+### Cleaner modeling code
+The modeling code could benefit from a touch-up and as a side effect, become ONNX exportable and hopefully slightly faster.
+
+### Experimental features (TBD)
+Today, voicepacks are essentially `(510, 256)`-shaped tensors, compiled as average styles per utterance length, with 510 possible lengths. Since most style vectors are computed on synthetic data, each style is essentially a "mean of means", which may explain why the voices are somewhat flat-sounding. It also implies that for any given utterance, currently the only features being used to choose how the voice sounds are (1) the user-selected voice name, like `af` and (2) the length of the utterance. Features like the punctuation texture `.?!` or the text sentiment are not yet being used. Potential solutions could be neural or even classical, e.g. using vector DBs. This, among other things, is still an area of research.
+
+### Community contributions welcome
+Within a couple weeks of Kokoro's Christmas 2024 release, talented people already [built](https://github.com/thewh1teagle/kokoro-onnx) [great](https://github.com/remsky/Kokoro-FastAPI) [things](https://github.com/lucasjinreal/Kokoros). If you want to build something, go for it! Kokoro is permissive Apache-licensed software. If you also want to add or improve something here (or [misaki](https://github.com/hexgrad/misaki)), hopefully Kokoro can earn your commit, and feel free to open a PR if so.