Automatic Speech Recognition
Transformers
Safetensors
VibeVoice
ASR
Transcriptoin
Diarization
Speech-to-Text
Instructions to use microsoft/VibeVoice-ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/VibeVoice-ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="microsoft/VibeVoice-ASR")# Load model directly from transformers import VibeVoiceForASRTraining model = VibeVoiceForASRTraining.from_pretrained("microsoft/VibeVoice-ASR", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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**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**.
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➡️ **Code:** [microsoft/VibeVoice](https://github.com/microsoft/VibeVoice)
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➡️ **Demo:** [VibeVoice-ASR-Demo](https://aka.ms/vibevoice-asr)
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**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**.
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➡️ **Code:** [microsoft/VibeVoice](https://github.com/microsoft/VibeVoice)<br>
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➡️ **Demo:** [VibeVoice-ASR-Demo](https://aka.ms/vibevoice-asr)
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