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Whisper Tiny De Emodb Emotion Classification

Developed by Flocksserver
A German emotion classification model fine-tuned on openai/whisper-tiny, achieving 91.59% accuracy on the Emo-DB dataset
Downloads 27
Release Time : 9/11/2024

Model Overview

This model is a German speech emotion classifier based on the Whisper-tiny architecture, specifically fine-tuned for the Emo-DB dataset to recognize emotional states in speech.

Model Features

High-Accuracy Emotion Recognition
Achieves 91.59% classification accuracy on the German Emo-DB test set
Lightweight Architecture
Based on the small Whisper-tiny architecture, suitable for deployment in resource-limited scenarios
Domain-Specific Optimization
Specifically fine-tuned for German emotion recognition tasks

Model Capabilities

German Speech Emotion Classification
Real-Time Audio Analysis
Multi-Emotion State Recognition

Use Cases

Affective Computing
Customer Service Call Analysis
Automatically identifies emotional states in customer calls
91.59% test accuracy
Psychological State Assessment
Assists psychologists in analyzing emotional features in patient speech
Human-Computer Interaction
Emotion-Aware Voice Assistants
Enables voice assistants to adjust responses based on user emotions
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