8Kdl/month
27likes
Identifier
Model ID
pyannote/brouhahaTags
pyannote-audiopytorchpyannotepyannote-audio-modelaudiovoicespeechvoice-activity-detectionspeech-to-noise ratiosnrroom acousticsc50dataset:LibriSpeechdataset:AudioSetdataset:EchoThiefdataset:MIT-Acoustical-Reverberation-Scenearxiv:2210.13248license:openrailregion:us
Use brouhaha on Mixpeek
Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.
Open StudioHow It Runs on Mixpeek
On Mixpeek, brouhaha runs as a managed extractor inside a processing pipeline. Point a bucket of voice activity detection data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.
Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.
Specification
Organizationpyannote
TaskVoice Activity Detection
Librarypyannote-audio
Licenseopenrail
Downloads/mo8K
Likes27
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