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Speech Emotion Recognition With Openai Whisper Large V3

Developed by firdhokk
This project utilizes the Whisper model for speech emotion recognition, capable of classifying audio into different emotional categories such as happiness, sadness, and surprise.
Downloads 7,750
Release Time : 9/21/2024

Model Overview

This model is a fine-tuned version of OpenAI Whisper Large V3 for speech emotion recognition, accurately identifying emotional categories in speech.

Model Features

High Accuracy Emotion Recognition
The model achieves 91.99% accuracy on the test set, effectively recognizing various speech emotions.
Based on Whisper Architecture
Leverages the powerful audio processing capabilities of Whisper Large V3 through fine-tuning, inheriting its excellent feature extraction.
Multi-dataset Training
Trained on multiple speech emotion datasets including RAVDESS, SAVEE, TESS, and URDU to enhance generalization.

Model Capabilities

Speech Emotion Recognition
Audio Classification
Multi-emotion Category Recognition

Use Cases

Mental Health Analysis
Psychological Counseling Assistance
Assists psychologists in assessing clients' emotional states by analyzing changes in speech emotions.
Accurately identifies 7 primary emotional states
Customer Service
Customer Service Quality Monitoring
Automatically analyzes emotional changes in customer service calls to evaluate service quality.
Real-time monitoring of agent emotional states
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