microsoft/VibeVoicePublic

Open-Source Frontier Voice AI

AI summary: Open-source frontier voice AI models for long-form speech recognition and synthesis.

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PythonMITCreated Aug 25, 2025Last push 1mo ago+118 stars this week+1K this month

Quick answers

What is VibeVoice?
Open-source frontier voice AI models for long-form speech recognition and synthesis.
What does VibeVoice do?
VibeVoice is a suite of advanced, open-source voice AI models developed by Microsoft, encompassing both Text-to-Speech (TTS) and Automatic Speech Recognition (ASR). It utilizes continuous speech tokenizers operating at an ultra-low 7.5 Hz frame rate and a next-token diffusion framework to efficiently process exceptionally long audio sequences. The ASR model can ingest up to 60 minutes of audio in a single pass within a 64K token length to generate rich transcriptions including speaker diarization and timestamps. Meanwhile, the Realtime TTS models offer robust, multi-speaker conversational generation for up to 90 minutes. It inherently supports customized hotwords allowing users to provide domain-specific vocabulary to significantly improve transcription accuracy.
Who is VibeVoice for?
AI researchers, software engineers, and enterprise developers building advanced conversational AI interfaces, transcription services, and accessibility tools requiring robust handling of long-form audio.
How do I get started with VibeVoice?
https://github.com/microsoft/VibeVoice/blob/main/docs/vibevoice-asr.md
How popular is VibeVoice on GitHub?
microsoft/VibeVoice has 54,602 stars and 6,138 forks on GitHub, and gained 118 stars in the last 7 days.
What license does VibeVoice use?
microsoft/VibeVoice is released under the MIT license.

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    13 trending appearances

What VibeVoice does

VibeVoice is a suite of advanced, open-source voice AI models developed by Microsoft, encompassing both Text-to-Speech (TTS) and Automatic Speech Recognition (ASR). It utilizes continuous speech tokenizers operating at an ultra-low 7.5 Hz frame rate and a next-token diffusion framework to efficiently process exceptionally long audio sequences. The ASR model can ingest up to 60 minutes of audio in a single pass within a 64K token length to generate rich transcriptions including speaker diarization and timestamps. Meanwhile, the Realtime TTS models offer robust, multi-speaker conversational generation for up to 90 minutes. It inherently supports customized hotwords allowing users to provide domain-specific vocabulary to significantly improve transcription accuracy.

AI researchers, software engineers, and enterprise developers building advanced conversational AI interfaces, transcription services, and accessibility tools requiring robust handling of long-form audio.

  • Long-form ASR processing: Analyzes up to 60 minutes of continuous audio in a single pass, preventing the loss of global context common in chunked models.
  • Rich structured transcription: Simultaneously performs speech recognition, speaker diarization (who), and timestamping (when) in a single output.
  • Custom hotword guidance: Allows users to input specific domain vocabulary or names to heavily bias and improve recognition accuracy.
  • Ultra-low frame rate tokenization: Uses acoustic and semantic tokenizers at 7.5 Hz to maintain high audio fidelity while reducing computational load.
  • Multi-speaker TTS: Supports up to 4 distinct speakers in a single conversation with natural turn-taking and speaker consistency across long dialogues.
  • Edge deployment capability: Offers a specialized BitNet ASR variant optimized for real-time inference on standard edge CPUs without requiring a GPU.

Where teams use it

Meeting transcription

Transcribe and diarize entire hour-long corporate meetings in a single pass with highly accurate speaker attribution.

Podcast processing

Convert long-form conversational podcasts into structured text formats suitable for immediate publishing or indexing.

Domain-specific dictation

Utilize custom hotwords to accurately transcribe highly technical medical or legal audio recordings.

Edge AI integration

Deploy the VibeVoice-ASR-BitNet engine on local, low-power devices for offline, real-time transcription.

Conversational audio generation

Synthesize long-form multi-speaker podcasts or dialogues up to 90 minutes using the VibeVoice-TTS system.

Getting started: https://github.com/microsoft/VibeVoice/blob/main/docs/vibevoice-asr.md

README

main branch

🎙️ VibeVoice: Open-Source Frontier Voice AI

Project Page Hugging Face TTS Report ASR Report Colab ASR Playground

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.

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Commits per week

last 52 weeks
310Week of 2025-10-05: 0 commitsWeek of 2025-10-12: 0 commitsWeek of 2025-10-19: 0 commitsWeek of 2025-10-26: 0 commitsWeek of 2025-11-02: 0 commitsWeek of 2025-11-09: 0 commitsWeek of 2025-11-16: 0 commitsWeek of 2025-11-23: 0 commitsWeek of 2025-11-30: 7 commitsWeek of 2025-12-07: 8 commitsWeek of 2025-12-14: 2 commitsWeek of 2025-12-21: 0 commitsWeek of 2025-12-28: 0 commitsWeek of 2026-01-04: 0 commitsWeek of 2026-01-11: 0 commitsWeek of 2026-01-18: 31 commitsWeek of 2026-01-25: 17 commitsWeek of 2026-02-01: 7 commitsWeek of 2026-02-08: 1 commitsWeek of 2026-02-15: 0 commitsWeek of 2026-02-22: 1 commitsWeek of 2026-03-01: 1 commitsWeek of 2026-03-08: 0 commitsWeek of 2026-03-15: 0 commitsWeek of 2026-03-22: 9 commitsWeek of 2026-03-29: 28 commitsWeek of 2026-04-05: 5 commitsWeek of 2026-04-12: 4 commitsWeek of 2026-04-19: 1 commitsWeek of 2026-04-26: 0 commitsWeek of 2026-05-03: 1 commitsWeek of 2026-05-10: 0 commitsWeek of 2026-05-17: 0 commitsWeek of 2026-05-24: 0 commitsWeek of 2026-05-31: 0 commitsWeek of 2026-06-07: 0 commitsWeek of 2026-06-14: 0 commitsWeek of 2026-06-21: 0 commitsWeek of 2026-06-28: 0 commitsWeek of 2026-07-05: 0 commitsWeek of 2026-07-12: 0 commitsWeek of 2026-07-19: 3 commitsWeek of 2026-07-26: 0 commitsWeek of 2026-08-02: 0 commitsWeek of 2026-08-09: 0 commitsWeek of 2026-08-16: 0 commitsWeek of 2026-08-23: 3 commitsWeek of 2026-08-30: 12 commitsWeek of 2026-09-06: 0 commitsWeek of 2026-09-13: 0 commitsWeek of 2026-09-20: 0 commitsWeek of 2026-09-27: 0 commitsOct 5, 2025Sep 27, 2026
141 commits in the last 52 weeks.

When work happens

weekday and hour
SunMonTueWedThuFriSat036912151821Sun 0:00 — 1 commitsSun 1:00 — 2 commitsSun 2:00 — 1 commitsSun 3:00 — 1 commitsSun 4:00 — 0 commitsSun 5:00 — 1 commitsSun 6:00 — 1 commitsSun 7:00 — 0 commitsSun 8:00 — 0 commitsSun 9:00 — 1 commitsSun 10:00 — 0 commitsSun 11:00 — 0 commitsSun 12:00 — 0 commitsSun 13:00 — 0 commitsSun 14:00 — 0 commitsSun 15:00 — 0 commitsSun 16:00 — 2 commitsSun 17:00 — 0 commitsSun 18:00 — 5 commitsSun 19:00 — 5 commitsSun 20:00 — 0 commitsSun 21:00 — 3 commitsSun 22:00 — 1 commitsSun 23:00 — 0 commitsMon 0:00 — 0 commitsMon 1:00 — 0 commitsMon 2:00 — 0 commitsMon 3:00 — 2 commitsMon 4:00 — 0 commitsMon 5:00 — 0 commitsMon 6:00 — 1 commitsMon 7:00 — 1 commitsMon 8:00 — 2 commitsMon 9:00 — 0 commitsMon 10:00 — 0 commitsMon 11:00 — 0 commitsMon 12:00 — 0 commitsMon 13:00 — 3 commitsMon 14:00 — 1 commitsMon 15:00 — 0 commitsMon 16:00 — 0 commitsMon 17:00 — 0 commitsMon 18:00 — 1 commitsMon 19:00 — 0 commitsMon 20:00 — 1 commitsMon 21:00 — 0 commitsMon 22:00 — 0 commitsMon 23:00 — 1 commitsTue 0:00 — 3 commitsTue 1:00 — 0 commitsTue 2:00 — 1 commitsTue 3:00 — 0 commitsTue 4:00 — 1 commitsTue 5:00 — 1 commitsTue 6:00 — 0 commitsTue 7:00 — 0 commitsTue 8:00 — 0 commitsTue 9:00 — 0 commitsTue 10:00 — 1 commitsTue 11:00 — 1 commitsTue 12:00 — 5 commitsTue 13:00 — 0 commitsTue 14:00 — 0 commitsTue 15:00 — 1 commitsTue 16:00 — 0 commitsTue 17:00 — 1 commitsTue 18:00 — 0 commitsTue 19:00 — 0 commitsTue 20:00 — 2 commitsTue 21:00 — 2 commitsTue 22:00 — 0 commitsTue 23:00 — 0 commitsWed 0:00 — 0 commitsWed 1:00 — 0 commitsWed 2:00 — 0 commitsWed 3:00 — 0 commitsWed 4:00 — 0 commitsWed 5:00 — 0 commitsWed 6:00 — 1 commitsWed 7:00 — 1 commitsWed 8:00 — 2 commitsWed 9:00 — 2 commitsWed 10:00 — 3 commitsWed 11:00 — 1 commitsWed 12:00 — 0 commitsWed 13:00 — 0 commitsWed 14:00 — 0 commitsWed 15:00 — 0 commitsWed 16:00 — 0 commitsWed 17:00 — 0 commitsWed 18:00 — 1 commitsWed 19:00 — 2 commitsWed 20:00 — 0 commitsWed 21:00 — 2 commitsWed 22:00 — 5 commitsWed 23:00 — 5 commitsThu 0:00 — 8 commitsThu 1:00 — 6 commitsThu 2:00 — 2 commitsThu 3:00 — 2 commitsThu 4:00 — 0 commitsThu 5:00 — 4 commitsThu 6:00 — 1 commitsThu 7:00 — 1 commitsThu 8:00 — 0 commitsThu 9:00 — 0 commitsThu 10:00 — 1 commitsThu 11:00 — 0 commitsThu 12:00 — 0 commitsThu 13:00 — 0 commitsThu 14:00 — 0 commitsThu 15:00 — 0 commitsThu 16:00 — 1 commitsThu 17:00 — 1 commitsThu 18:00 — 4 commitsThu 19:00 — 1 commitsThu 20:00 — 0 commitsThu 21:00 — 1 commitsThu 22:00 — 1 commitsThu 23:00 — 0 commitsFri 0:00 — 0 commitsFri 1:00 — 1 commitsFri 2:00 — 1 commitsFri 3:00 — 0 commitsFri 4:00 — 0 commitsFri 5:00 — 1 commitsFri 6:00 — 1 commitsFri 7:00 — 2 commitsFri 8:00 — 0 commitsFri 9:00 — 1 commitsFri 10:00 — 1 commitsFri 11:00 — 0 commitsFri 12:00 — 1 commitsFri 13:00 — 2 commitsFri 14:00 — 1 commitsFri 15:00 — 0 commitsFri 16:00 — 3 commitsFri 17:00 — 2 commitsFri 18:00 — 1 commitsFri 19:00 — 0 commitsFri 20:00 — 0 commitsFri 21:00 — 2 commitsFri 22:00 — 0 commitsFri 23:00 — 0 commitsSat 0:00 — 0 commitsSat 1:00 — 0 commitsSat 2:00 — 0 commitsSat 3:00 — 0 commitsSat 4:00 — 0 commitsSat 5:00 — 3 commitsSat 6:00 — 0 commitsSat 7:00 — 0 commitsSat 8:00 — 1 commitsSat 9:00 — 0 commitsSat 10:00 — 0 commitsSat 11:00 — 0 commitsSat 12:00 — 1 commitsSat 13:00 — 0 commitsSat 14:00 — 0 commitsSat 15:00 — 1 commitsSat 16:00 — 0 commitsSat 17:00 — 1 commitsSat 18:00 — 0 commitsSat 19:00 — 1 commitsSat 20:00 — 0 commitsSat 21:00 — 1 commitsSat 22:00 — 0 commitsSat 23:00 — 0 commits
Commit volume by weekday and hour (UTC). Larger dots mean more commits.
DateListRankStars gained
Aug 3, 2026weekly#12+1,317
Aug 2, 2026weekly#12+1,317
Aug 1, 2026weekly#14+1,222
Jul 31, 2026daily#5+336
Jul 30, 2026daily#5+336
Apr 29, 2026daily#13+88
Apr 28, 2026daily#7+135
Apr 26, 2026daily#9+225
Mar 31, 2026daily#6+387
Mar 30, 2026daily#3+351
Mar 29, 2026daily#8+307
Jan 25, 2026daily#23+159
Jan 24, 2026daily#23+150