Hubert Emotion
A speech emotion recognition model based on the HuBERT architecture, capable of identifying the emotional state of a speaker from audio.
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Release Time : 3/2/2022
Model Overview
This model is trained using the HuBERT architecture and is specifically designed for speech emotion classification tasks. It can recognize various emotional states such as sadness, fear, etc., and provides probability scores for each emotion.
Model Features
High-Precision Emotion Recognition
Accurately identifies various speech emotion states such as sadness, fear, etc.
Based on HuBERT Architecture
Utilizes the powerful feature extraction capabilities of the HuBERT model for emotion classification.
Probability Output
Provides probability scores for each emotion, not just a single classification result.
Model Capabilities
Speech Emotion Recognition
Audio Classification
Probability Score Output
Use Cases
Mental Health
Emotional State Monitoring
Monitors user's emotional changes through voice analysis
Can identify negative emotions such as sadness and fear
Human-Computer Interaction
Emotion-Aware Voice Assistant
Enables voice assistants to adjust responses based on user emotions
Enhances interaction experience
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