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Hubert Base Ch Speech Emotion Recognition

Developed by xmj2002
A Chinese speech emotion classification model fine-tuned on the CASIA dataset using Tencent Game Partner's pre-trained Chinese HuBERT model, supporting 6 emotion categories.
Downloads 710
Release Time : 5/15/2023

Model Overview

This model is specifically designed for Chinese speech emotion recognition, capable of accurately classifying six emotional states: anger, fear, happiness, calmness, sadness, and surprise.

Model Features

High Accuracy
Achieves 97.2% accuracy on the test set, demonstrating excellent performance.
Professional Dataset Training
Trained using the CASIA dataset performed by professional actors, ensuring high data quality.
Chinese Optimization
Based on the Chinese HuBERT pre-trained model, optimized for Chinese speech characteristics.

Model Capabilities

Chinese speech emotion recognition
Six-emotion classification
Audio feature extraction

Use Cases

Human-Computer Interaction
Intelligent Customer Service Emotion Analysis
Analyze emotional states in customer voices to improve service quality
Accurately identifies emotions like anger and happiness, helping customer service adjust strategies promptly.
Mental Health
Emotional State Monitoring
Track user emotional changes through speech analysis
Identifies negative emotions like sadness and fear, assisting psychological evaluation.
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