Distilhubert Finetuned Ravdess
A speech emotion recognition model fine-tuned on the RAVDESS dataset based on DistilHuBERT architecture, achieving 92.36% accuracy
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Release Time : 6/21/2023
Model Overview
This model is a fine-tuned version of DistilHuBERT, specifically designed for speech emotion recognition tasks, demonstrating excellent performance on the RAVDESS dataset.
Model Features
High Accuracy
Achieves 92.36% classification accuracy on the RAVDESS evaluation set
Lightweight Architecture
Based on the lightweight DistilHuBERT architecture, reducing computational requirements while maintaining performance
Speech Emotion Recognition
Optimized specifically for speech emotion recognition tasks
Model Capabilities
Speech Emotion Classification
Audio Feature Extraction
Use Cases
Sentiment Analysis
Customer Service Emotion Monitoring
Real-time analysis of customer emotional states during service calls
Can identify basic emotions such as anger, happiness, sadness
Mental Health Assessment
Evaluate speaker's psychological state through voice analysis
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