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Distilhubert Finetuned Ravdess
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Distilhubert Finetuned Ravdess

Developed by pollner
A speech emotion recognition model fine-tuned on the RAVDESS dataset based on DistilHuBERT architecture, achieving 92.36% accuracy
Audio Classification
Transformers
Open Source License:Apache-2.0#Speech Emotion Recognition#High Accuracy#Lightweight Model
Downloads 43
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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