1Kdl/month
51likes
Identifier
Model ID
BUT-FIT/diarizen-wavlm-large-s80-mdTags
transformerspytorchspeakerspeaker-diarizationmeetingwavlmwespeakerdiarizenpyannotepyannote-audio-pipelinevoice-activity-detectionarxiv:2505.24111arxiv:2506.18623license:cc-by-nc-4.0endpoints_compatibleregion:us
Use diarizen-wavlm-large-s80-md 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, diarizen-wavlm-large-s80-md 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
OrganizationBUT-FIT
TaskVoice Activity Detection
Librarytransformers
Licensecc-by-nc-4.0
Downloads/mo1K
Likes51
View on HuggingFace
See model card, files, and community discussion
Related Voice Activity Detection Models
pyannote/segmentation-3.0
5.9M
pyannote/segmentation
3.9M
videosdk-live/Namo-Turn-Detector-v1-Korean
423K
software-mansion/react-native-executorch-fsmn-vad
35K
aufklarer/Silero-VAD-v5-MLX
34K
FluidInference/silero-vad-coreml
30K
pyannote/speaker-diarization-precision-2
25K
FluidInference/speaker-diarization-coreml
18K