microsoft/VibeVoice

Overview

VibeVoice is a family of open-source frontier voice AI models that includes both Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) models.

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.

For more information, demos, and examples, please visit our Project Page.

Models

1. 📖 VibeVoice-ASR - Long-form Speech Recognition

VibeVoice-ASR is a unified speech-to-text model designed to handle 60-minute long-form audio in a single pass, generating structured transcriptions containing Who (Speaker), When (Timestamps), and What (Content), with support for Customized Hotwords.

• 🕒 60-minute Single-Pass Processing: Unlike conventional ASR models that slice audio into short chunks (often losing global context), VibeVoice ASR accepts up to 60 minutes of continuous audio input within 64K token length. This ensures consistent speaker tracking and semantic coherence across the entire hour.

• 👤 Customized Hotwords: Users can provide customized hotwords (e.g., specific names, technical terms, or background info) to guide the recognition process, significantly improving accuracy on domain-specific content.

• 📝 Rich Transcription (Who, When, What): The model jointly performs ASR, diarization, and timestamping, producing a structured output that indicates who said what and when.

📖 Documentation | 🤗 Hugging Face | 🎮 Playground | 🛠️ Finetuning | 📊 Paper

2. 🎙️ VibeVoice-TTS - Long-form Multi-speaker TTS

Best for: Long-form conversational audio, podcasts, multi-speaker dialogues

• ⏱️ 90-minute Long-form Generation: Synthesizes conversational/single-speaker speech up to 90 minutes in a single pass, maintaining speaker consistency and semantic coherence throughout.

• 👥 Multi-speaker Support: Supports up to 4 distinct speakers in a single conversation, with natural turn-taking and speaker consistency across long dialogues.

• 🎭 Expressive Speech: Generates expressive, natural-sounding speech that captures conversational dynamics and emotional nuances.

• 🌐 Multi-lingual Support: Supports English, Chinese and other languages.

📖 Documentation | 🤗 Hugging Face | 📊 Paper

English

Chinese

Cross-Lingual

Spontaneous Singing

Long Conversation with 4 people

3. ⚡ VibeVoice-Streaming - Real-time Streaming TTS

VibeVoice-Realtime is a lightweight real‑time text-to-speech model supporting streaming text input and robust long-form speech generation.

• Parameter size: 0.5B (deployment-friendly)
• Real-time TTS (~300 milliseconds first audible latency)
• Streaming text input
• Robust long-form speech generation (~10 minutes)

📖 Documentation | 🤗 Hugging Face | 🚀 Colab

Contributing

Please see CONTRIBUTING.md for detailed contribution guidelines.

⚠️ Risks and Limitations

While efforts have been made to optimize it through various techniques, it may still produce outputs that are unexpected, biased, or inaccurate. VibeVoice inherits any biases, errors, or omissions produced by its base model (specifically, Qwen2.5 1.5b in this release). Potential for Deepfakes and Disinformation: High-quality synthetic speech can be misused to create convincing fake audio content for impersonation, fraud, or spreading disinformation. Users must ensure transcripts are reliable, check content accuracy, and avoid using generated content in misleading ways. Users are expected to use the generated content and to deploy the models in a lawful manner, in full compliance with all applicable laws and regulations in the relevant jurisdictions. It is best practice to disclose the use of AI when sharing AI-generated content.

We do not recommend using VibeVoice in commercial or real-world applications without further testing and development. This model is intended for research and development purposes only. Please use responsibly.

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