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README.md

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 ## 👉🏻 IndexTTS2 👈🏻
 
 <center><h3>IndexTTS2: A Breakthrough in Emotionally Expressive and Duration-Controlled Auto-Regressive Zero-Shot Text-to-Speech</h3></center>
 
-[![IndexTTS2](assets/IndexTTS2_banner.png)](assets/IndexTTS2_banner.png)
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   <a href='https://arxiv.org/abs/2506.21619'>
     <img src='https://img.shields.io/badge/ArXiv-2506.21619-red?logo=arxiv'/>
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 **Tips:** Please contact authors for more detailed information. For commercial cooperation, please contact <u>indexspeech@bilibili.com</u>
 
-### Feel IndexTTS2
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-**IndexTTS2: The Future of Voice, Now Generating**
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-[![IndexTTS2 Demo](assets/IndexTTS2-video-pic.png)](assets/IndexTTS2.mp4)
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-*Click the image to watch IndexTTS2 video*
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 ### Contact
 QQ Group：553460296(No.1) 1048202584(No.2) 764630270(No.3)\
 Discord：https://discord.gg/uT32E7KDmy  \
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 - `2025/03/25` 🔥 We release **IndexTTS-1.0** model parameters and inference code.
 - `2025/02/12` 🔥 We submitted our paper on arXiv, and released our demos and test sets.
 
-## 🖥️ Method
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-The overview of IndexTTS2 is shown as follows.
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-The key contributions of **indextts2** are summarized as follows:
- - We propose a duration adaptation scheme for autoregressive TTS models. IndexTTS2 is the first autoregressive zero-shot TTS model to combine precise duration control with natural duration generation, and the method is scalable for any autoregressive large-scale TTS model.  
- - The emotional and speaker-related features are decoupled from the prompts, and a feature fusion strategy is designed to maintain semantic fluency and pronunciation clarity during emotionally rich expressions. Furthermore, a tool was developed for emotion control, utilising natural language descriptions for the benefit of users.  
- - To address the lack of highly expressive speech data, we propose an effective training strategy, significantly enhancing the emotional expressiveness of zeroshot TTS to State-of-the-Art (SOTA) level.  
- - We will publicly release the code and pre-trained weights to facilitate future research and practical applications.  
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 ## Acknowledge
 1. [tortoise-tts](https://github.com/neonbjb/tortoise-tts)
 2. [XTTSv2](https://github.com/coqui-ai/TTS)