S

Segmentation 3.0

Developed by tensorlake
This is a speaker segmentation model based on pyannote.audio, capable of detecting speech activity, speaker changes, and overlapping speech.
Downloads 387
Release Time : 7/25/2024

Model Overview

The model processes 10-second 16kHz sampled mono audio and outputs 7 types of speaker segmentation results, including non-speech, single speaker, and overlapping speaker detection.

Model Features

Multi-task processing
Simultaneously supports speech activity detection, speaker segmentation, and overlapping speech detection
Efficient processing
Optimized for 10-second audio segments, suitable for real-time processing
Multi-dataset training
Trained on multiple datasets including AISHELL, AliMeeting, and AMI, with strong generalization capabilities

Model Capabilities

Speech activity detection
Speaker segmentation
Overlapping speech detection
Speaker change detection

Use Cases

Meeting analysis
Meeting transcription
Automatically identifies different speakers in meetings
Improves meeting transcription efficiency
Speech analysis
Speech activity detection
Identifies speech segments in audio
Can be used for speech recognition preprocessing
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