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CREMA D Model
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CREMA D Model

Developed by jdmartinev
A speech emotion recognition model fine-tuned based on facebook/wav2vec2-base, achieving 73.22% accuracy on the evaluation set
Audio Classification
Transformers
Open Source License:Apache-2.0#Speech Emotion Recognition#wav2vec2 Fine-tuning#High Accuracy
Downloads 21
Release Time : 5/3/2023

Model Overview

This model is a speech emotion recognition model based on the wav2vec2 architecture, capable of identifying emotion categories from speech

Model Features

High Accuracy
Achieves 73.22% accuracy on the evaluation set, outperforming random guessing
Based on wav2vec2 Architecture
Uses the proven wav2vec2-base as the base model, with strong speech feature extraction capabilities
End-to-End Training
The model can directly learn from raw speech waveforms and predict emotion categories

Model Capabilities

Speech Emotion Recognition
Speech Feature Extraction
Emotion Classification

Use Cases

Human-Computer Interaction
Smart Customer Service Emotion Analysis
Analyzes the emotional state in customer speech to help the customer service system provide more human-like responses
Mental Health
Emotional State Monitoring
Analyzes users' emotional changes through speech for mental health applications
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