@@ -43,17 +36,6 @@ Existing autoregressive large-scale text-to-speech (TTS) models have advantages
**Tips:** Please contact authors for more detailed information. For commercial cooperation, please contact indexspeech@bilibili.com
-### Feel IndexTTS2
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-**IndexTTS2: The Future of Voice, Now Generating**
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-[](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 \
@@ -68,22 +50,6 @@ Emal:indexspeech@bilibili.com \
- `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)