@oliviscusAI: microsoft just released a tool that transcribes a full hour of audio at once, tracking who spoke and when. it's called …

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Summary

Microsoft released vibevoice, a 7B model that transcribes up to an hour of audio in one shot with built-in speaker diarization and timestamps, supporting 50+ languages and running locally without API costs.

microsoft just released a tool that transcribes a full hour of audio at once, tracking who spoke and when. it's called vibevoice the 7b model processes the full recording in one shot instead of chunking it, so speaker identity and context never break across segments → full speaker diarization built in, not bolted on → structured timestamps for every speaker turn → supports 50+ languages runs locally, no api costs.
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microsoft just released a tool that transcribes a full hour of audio at once, tracking who spoke and when.

it’s called vibevoice

the 7b model processes the full recording in one shot instead of chunking it, so speaker identity and context never break across segments

→ full speaker diarization built in, not bolted on → structured timestamps for every speaker turn → supports 50+ languages

runs locally, no api costs.

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Microsoft open-sourced VibeVoice, a unified speech-to-text model handling 60-minute audio in a single pass with speaker/timestamp/content transcription, and a real-time text-to-speech model supporting streaming input and multilingual voices. The project includes an edge CPU inference engine for ASR via quantization.

@uniswap12: Microsoft open-sourced a voice AI that can transcribe 60 minutes of long audio in one go, handling 4 people speaking simultaneously. VibeVoice, open-sourced by Microsoft, 24.8k stars, I only found out about it today. For converting recordings to text, I've been using Whisper, but it often times out on long meeting recordings and struggles with multi-speaker recognition...

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Microsoft open-sourced the VibeVoice speech AI framework, which supports one-shot transcription of 60-minute long audio, multi-speaker diarization and timestamp labeling, and also provides multi-role TTS synthesis capabilities. It is based on Qwen2.5 and comes with a 0.5B lightweight real-time version. It has received 24.8k stars on GitHub.

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VibeVoice is a new model from Microsoft that synthesizes long-form multi-speaker speech using next-token diffusion and a highly efficient continuous speech tokenizer. It achieves superior fidelity and compression, supporting up to 90 minutes of audio with multiple speakers.

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