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Speaker Segmentation Fine Tuned Callhome Jpn
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Speaker Segmentation Fine Tuned Callhome Jpn
Developed by kamilakesbi
This is a speaker diarization model fine-tuned from the pyannote/segmentation-3.0 base model, specifically optimized for Japanese telephone conversation scenarios.
Downloads 18
Release Time : 4/22/2024
Model Overview
This model is used for speaker diarization tasks in speech processing, capable of detecting speech activity, speaker changes, and overlapping speech, suitable for analyzing telephone conversation scenarios.
Model Features
Optimized for Japanese telephone conversations
Fine-tuned specifically for Japanese telephone conversation scenarios to improve speaker recognition accuracy in such contexts.
Overlapping speech detection
Capable of detecting overlapping speech segments where multiple speakers talk simultaneously.
Speaker change detection
Accurately identifies points in the conversation where speakers switch.
Model Capabilities
Speech activity detection
Speaker segmentation
Overlapping speech detection
Speaker change detection
Use Cases
Telephone conversation analysis
Customer service quality monitoring
Analyze dialogue patterns and quality in customer service calls
Identify different speakers and analyze dialogue structure and response times
Meeting transcription analysis
Automatically segment different speakers in meeting recordings
Generate speaker labels with timestamps
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