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@@ -10,10 +10,11 @@ A core innovation of VibeVoice is its use of continuous speech tokenizers (Acous
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  The model can synthesize speech up to **90 minutes** long with up to **4 distinct speakers**, surpassing the typical 1-2 speaker limits of many prior models.
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- ➡️ **Project Demo:** [microsoft/VibeVoice-Demo](https://microsoft.github.io/VibeVoice)
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- ➡️ **Github Code:** [microsoft/VibeVoice-Code](https://github.com/microsoft/VibeVoice)
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  ## Training details
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  Transformer-based Large Language Model (LLM) integrated with specialized acoustic and semantic tokenizers and a diffusion-based decoding head.
 
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  The model can synthesize speech up to **90 minutes** long with up to **4 distinct speakers**, surpassing the typical 1-2 speaker limits of many prior models.
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+ ➡️ **Technical Report:** [VibeVoice Technical Report](https://github.com/microsoft/VibeVoice/blob/main/report/TechnicalReport.pdf)
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+ ➡️ **Project Page:** [microsoft/VibeVoice](https://microsoft.github.io/VibeVoice)
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+ ➡️ **Code:** [microsoft/VibeVoice-Code](https://github.com/microsoft/VibeVoice)
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  ## Training details
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  Transformer-based Large Language Model (LLM) integrated with specialized acoustic and semantic tokenizers and a diffusion-based decoding head.