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Urdu Emotions Whisper Medium
Urdu emotion recognition model fine-tuned on Whisper-medium, achieving 91.67% accuracy on the evaluation set
Downloads 43
Release Time : 3/14/2024
Model Overview
This model is specifically designed for Urdu speech emotion classification, fine-tuned on OpenAI's Whisper-medium architecture, suitable for speech emotion analysis scenarios.
Model Features
High Accuracy
Achieves 91.67% classification accuracy on Urdu emotion datasets
Based on Whisper Architecture
Utilizes the mature Whisper-medium speech model for fine-tuning
Lightweight Training
Requires only 10 training epochs to achieve good results
Model Capabilities
Urdu Speech Recognition
Speech Emotion Classification
Audio Feature Extraction
Use Cases
Emotion Analysis
Customer Service Emotion Monitoring
Analyze customer emotional states during service calls
Can identify 91.67% of emotion categories in real-time
Mental Health Assessment
Evaluate speaker's emotional state through speech analysis
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