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Astie Finetuned On Shemo

Developed by minoosh
This model is a fine-tuned version of the AST model on the shEMO dataset, primarily used for speech emotion recognition tasks.
Downloads 24
Release Time : 4/27/2023

Model Overview

ASTie is a speech emotion recognition model based on the Audio Spectrogram Transformer (AST) architecture, fine-tuned on the shEMO dataset, capable of identifying emotional features in speech.

Model Features

High Accuracy
Achieves 81.67% accuracy on the evaluation set.
Efficient Inference
Can process approximately 8 samples per second.
AST-based Architecture
Utilizes the advanced Audio Spectrogram Transformer architecture.

Model Capabilities

Speech Emotion Recognition
Audio Classification

Use Cases

Emotion Analysis
Customer Service Emotion Monitoring
Real-time analysis of customer emotions in service calls.
81.67% recognition accuracy.
Psychological State Assessment
Evaluates the speaker's psychological state through voice analysis.
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