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SWivid committed Oct 16, 2024
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# F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching

<div style="position: relative; width: 100%;">
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<img src="https://avatars.githubusercontent.com/u/35554183?s=200&v=4" alt="Watermark" style="width: 140px; height: auto;">
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[![python](https://img.shields.io/badge/Python-3.10-brightgreen)](https://github.com/SWivid/F5-TTS)
[![arXiv](https://img.shields.io/badge/arXiv-2410.06885-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2410.06885)
[![demo](https://img.shields.io/badge/GitHub-Demo%20page-blue.svg)](https://swivid.github.io/F5-TTS/)
[![space](https://img.shields.io/badge/🤗-Space%20demo-yellow)](https://huggingface.co/spaces/mrfakename/E2-F5-TTS)
[![lab](https://img.shields.io/badge/X--LANCE-Lab-grey?labelColor=lightgrey)](https://x-lance.sjtu.edu.cn/)

**F5-TTS**: Diffusion Transformer with ConvNeXt V2, faster trained and inference.

**E2 TTS**: Flat-UNet Transformer, closest reproduction.
**E2 TTS**: Flat-UNet Transformer, closest reproduction from [paper](https://arxiv.org/abs/2406.18009).

**Sway Sampling**: Inference-time flow step sampling strategy, greatly improves performance

### Thanks to all the contributors !

## Installation

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