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GitHub - microsoft/VibeVoice: Open-Source Frontier Voice AI
tosh · 2026-04-28 · via Hacker News: Best
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📰 News

2026-03-06: 🚀 VibeVoice ASR is now part of a Transformers release! You can now use our speech recognition model directly through the Hugging Face Transformers library for seamless integration into your projects.

2026-01-21: 📣 We open-sourced VibeVoice-ASR, 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 User-Customized Context. Try it in Playground.

2025-12-16: 📣 We added experimental speakers to VibeVoice‑Realtime‑0.5B for exploration, including multilingual voices in nine languages (DE, FR, IT, JP, KR, NL, PL, PT, ES) and 11 distinct English style voices. Try it. More speaker types will be added over time.

2025-12-03: 📣 We open-sourced VibeVoice‑Realtime‑0.5B, a real‑time text‑to‑speech model that supports streaming text input and robust long-form speech generation. Try it on Colab.

2025-09-05: VibeVoice is an open-source research framework intended to advance collaboration in the speech synthesis community. After release, we discovered instances where the tool was used in ways inconsistent with the stated intent. Since responsible use of AI is one of Microsoft’s guiding principles, we have removed the VibeVoice-TTS code from this repository.

2025-08-25: 📣 We open-sourced VibeVoice-TTS, a long-form multi-speaker text-to-speech model that can synthesize speech up to 90 minutes long with up to 4 distinct speakers. — accepted as an Oral at ICLR 2026! 🔥

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.

Model Weight Quick Try
VibeVoice-ASR-7B HF Link Playground
VibeVoice-TTS-1.5B HF Link Disabled
VibeVoice-Realtime-0.5B HF Link Colab

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

DER
cpWER
tcpWER

small.mp4

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

VibeVoice Results

English

ES_._3.mp4

Chinese

default.mp4

Cross-Lingual

1p_EN2CH.mp4

Spontaneous Singing

2p_see_u_again.mp4

Long Conversation with 4 people

4p_climate_45min.mp4

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

VibeVoice_Realtime.mp4

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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