Wav2vec2 Xlsr English Speech Emotion Recognition
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Wav2vec2 Xlsr English Speech Emotion Recognition
Developed by AreejB
This model is used to recognize six basic emotions from English audio: anger, disgust, fear, happiness, sadness, and surprise, trained on the RAVDESS dataset.
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Release Time : 5/10/2024
Model Overview
An English speech emotion recognition model using the Wav2Vec2 architecture, capable of extracting emotional features from audio recordings and performing classification.
Model Features
Multi-emotion Recognition
Capable of recognizing six basic emotions: anger, disgust, fear, happiness, sadness, and surprise.
Based on Wav2Vec2 Architecture
Utilizes a pre-trained Wav2Vec2 model for fine-tuning, with excellent speech feature extraction capabilities.
High Accuracy
Achieves an average accuracy of 84.84% on the test set, with some emotion recognition precision exceeding 90%.
Model Capabilities
English Speech Emotion Recognition
Audio Feature Extraction
Multi-class Emotion Analysis
Use Cases
Human-Computer Interaction
Intelligent Customer Service Emotion Analysis
Analyze the emotional state in customer voice to improve service quality.
Can recognize key emotions such as anger and happiness, helping customer service adjust strategies promptly.
Mental Health
Emotional State Monitoring
Analyze users' emotional changes through speech.
Can recognize negative emotions such as sadness and fear, assisting in psychological assessment.
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