Voice Activity Detection
Voice activity detection model based on pyannote.audio 2.1, used to identify speech activity segments in audio
Downloads 7.7M
Release Time : 3/2/2022
Model Overview
This model is primarily used to detect speech activity in audio, accurately identifying the start and end times of speech segments, suitable for preprocessing steps in speech processing workflows
Model Features
High-Precision Speech Detection
Accurately detects speech activity segments in audio
End-to-End Processing
Provides a complete end-to-end voice activity detection solution
Easy Integration
Offers a simple Python interface for easy integration into existing systems
Model Capabilities
Voice Activity Detection
Audio Time Stamping
Speech/Non-Speech Classification
Use Cases
Speech Processing
Automatic Speech Recognition Preprocessing
Detects speech activity before ASR systems to improve recognition efficiency
Reduces processing overhead for non-speech segments
Meeting Transcript Analysis
Marks speech segments in meeting recordings
Facilitates subsequent speaker analysis and content extraction
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