Update README.md

Author: lucasnewman

README.md

@@ -1,2 +1,68 @@
-# f5-tts-swift
-Implementation of F5-TTS in Swift using MLX
+
+# F5 TTS for Swift (WIP)
+
+Implementation of [F5-TTS](https://arxiv.org/abs/2410.06885) in Swift, using the [MLX Swift]([https://github.com/ml-explore/mlx](https://github.com/ml-explore/mlx-swift)) framework.
+
+You can listen to a [sample here](https://s3.amazonaws.com/lucasnewman.datasets/f5tts/sample.wav) that was generated in ~11 seconds on an M3 Max MacBook Pro.
+
+See the [Python repository](https://github.com/lucasnewman/f5-tts-mlx) for additional details on the model architecture.
+This repository is based on the original Pytorch implementation available [here](https://github.com/SWivid/F5-TTS).
+
+
+## Installation
+
+The `F5TTS` Swift package can be built and run from Xcode or SwiftPM.
+
+A pretrained model is available [on Huggingface](https://hf.co/lucasnewman/f5-tts-mlx).
+
+
+## Usage
+
+```swift
+import Vocos
+import F5TTS
+
+let f5tts = try await F5TTS.fromPretrained(repoId: "lucasnewman/f5-tts-mlx")
+let vocos = try await Vocos.fromPretrained(repoId: "lucasnewman/vocos-mel-24khz-mlx") // if decoding to audio output
+
+let inputAudio = MLXArray(...)
+
+let (outputAudio, _) = f5tts.sample(
+    cond: inputAudio,
+    text: ["This is the caption for the reference audio and generation text."],
+    duration: ...,
+    vocoder: vocos.decode) { progress in
+        print("Progress: \(Int(progress * 100))%")
+    }
+```
+
+## Appreciation
+
+[Yushen Chen](https://github.com/SWivid) for the original Pytorch implementation of F5 TTS and pretrained model.
+
+[Phil Wang](https://github.com/lucidrains) for the E2 TTS implementation that this model is based on.
+
+## Citations
+
+```bibtex
+@article{chen-etal-2024-f5tts,
+      title={F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching}, 
+      author={Yushen Chen and Zhikang Niu and Ziyang Ma and Keqi Deng and Chunhui Wang and Jian Zhao and Kai Yu and Xie Chen},
+      journal={arXiv preprint arXiv:2410.06885},
+      year={2024},
+}
+```
+
+```bibtex
+@inproceedings{Eskimez2024E2TE,
+    title   = {E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS},
+    author  = {Sefik Emre Eskimez and Xiaofei Wang and Manthan Thakker and Canrun Li and Chung-Hsien Tsai and Zhen Xiao and Hemin Yang and Zirun Zhu and Min Tang and Xu Tan and Yanqing Liu and Sheng Zhao and Naoyuki Kanda},
+    year    = {2024},
+    url     = {https://api.semanticscholar.org/CorpusID:270738197}
+}
+```
+
+## License
+
+The code in this repository is released under the MIT license as found in the
+[LICENSE](LICENSE) file.