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microsoft VibeVoice

Open-Source Frontier Voice AI

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Python

License: MIT License

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  • popularity 87
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  • activity 100
  • freshness 100
  • community 60

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Trending

🎙️ VibeVoice: Open-Source Frontier Voice AI

microsoft%2FVibeVoice | Trendshift

VibeVoice Logo

📰 News

2026-09-03: 🚀 We released VibeVoice-ASR-Streaming, a unified streaming ASR model that continuously transcribes ''who said what'' as speech arrives, with support for customized hotwords and 10 languages. [Demo] [Models] [Report]

2026-07-23: ⚡ We released VibeVoice-ASR-BitNet, an edge CPU inference engine for VibeVoice-ASR. Through heterogeneous quantization (I8_S + I2_S), the model is compressed from 4.62 GB to 1.58 GB with real-time inference (RTF < 1) on 3+ CPU threads — no GPU required. [Code] [Models] [Report]

2026-03-12: 🚀 VibeVoice-ASR is now integrated into Azure AI Foundry Labs! You can now explore and test our unified speech-to-text capabilities directly through Microsoft Foundry.

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-ASR-Streaming HF Link Documentation
VibeVoice-ASR-BitNet (CPU) HF Link VibeASR.cpp
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.

  • 🎤 Streaming Recognition: A streaming variant transcribes while the audio is still arriving, emitting text once per audio chunk rather than waiting for the recording to end.

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

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.

Star History

Star History Chart

Created: Aug 25, 2025

Last push: Sep 3, 2026

Default branch: main

Repository Radar analysis

Deterministic insights derived from public metadata and our observations — not personal testing or reviews.

Why this repository is interesting

  • High absolute popularity (53,651 stars) signals broad adoption.
  • Maintained recently (last push 2 weeks ago).

Who should use it

  • Developers working primarily with Python

Potential use cases

  • Reference or evaluate Python open-source approaches in this domain

Strengths

  • Recent repository activity
  • README present in our index
  • Declared license: MIT License
  • Substantial fork count (6,053) suggests reuse and contribution interest

Limitations / considerations

  • Insights are derived from public metadata and our observations — not a substitute for code review

What to watch

  • Re-check last push, issues, and releases on GitHub before production adoption

Strong signals: Strong community interest · Active maintenance

Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.

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