# VibeVoice

# VibeVoice: A Frontier Open-Source Text-to-Speech Model

📄 Report ·
Code · 🤗 Hugging Face · Demo

VibeVoice is a novel framework designed for generating expressive, long-form, multi-speaker conversational audio, such as podcasts, from text. It addresses significant challenges in traditional Text-to-Speech (TTS) systems, particularly in scalability, speaker consistency, and natural turn-taking. A core innovation of VibeVoice is its use of continuous speech tokenizers (Acoustic and Semantic) operating at an ultra-low frame rate of 7.5 Hz. These tokenizers efficiently preserve audio fidelity while significantly boosting computational efficiency for processing long sequences. VibeVoice employs a next-token diffusion framework, leveraging a Large Language Model (LLM) to understand textual context and dialogue flow, and a diffusion head to generate high-fidelity acoustic details. 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.

## Context-Aware Expression

### Spontaneous Emotion

### Spontaneous Singing

## Podcast with Background Music

### Example 1

### Example 2

## Cross-Lingual

### Mandarin to English

### English to Mandarin

## Long Conversational Speech

* Timestamps are derived from the generated audio and may contain errors.