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Overlapped Speech Detection
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Overlapped Speech Detection

Developed by pyannote
A pre-trained model for detecting overlapped speech in audio, capable of identifying time segments where two or more speakers are active simultaneously.
Speaker AnalysisOpen Source License:MIT#Overlapped speech detection#Speaker diarization#End-to-end model
Downloads 144.68k
Release Time : 3/2/2022

Model Overview

This model is primarily used to detect overlapped speech segments in audio, where two or more speakers are talking simultaneously. Suitable for speech processing, speaker diarization, and related tasks.

Model Features

Overlapped speech detection
Accurately identifies time segments where two or more speakers are active simultaneously in audio
End-to-end training
Uses end-to-end training to learn features directly from raw audio
Pre-trained model
Provides an out-of-the-box pre-trained model, eliminating the need for training from scratch

Model Capabilities

Overlapped speech detection
Speaker diarization
Audio timeline analysis

Use Cases

Speech processing
Meeting transcript analysis
Analyzes overlapped dialogue segments in meeting recordings to improve transcription accuracy
Can identify segments where multiple people speak simultaneously
Speaker diarization
Provides overlapped speech detection functionality for speaker diarization systems
Improves the accuracy of speaker segmentation
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