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Finetuned Wav2vec2.0 Base On IEMOCAP 2
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Finetuned Wav2vec2.0 Base On IEMOCAP 2

Developed by minoosh
This is a speech emotion recognition model based on the facebook/wav2vec2-base model fine-tuned on the IEMOCAP dataset, achieving 73.9% accuracy on the evaluation set.
Audio Classification
Transformers
Open Source License:Apache-2.0#Speech Emotion Recognition#High Accuracy#IEMOCAP Dataset
Downloads 32
Release Time : 6/10/2023

Model Overview

This model is primarily used for speech emotion recognition tasks, capable of identifying and classifying different emotional states from speech signals.

Model Features

High Accuracy
Achieves 73.9% accuracy on the evaluation set, outperforming the baseline model.
Based on wav2vec2.0 Architecture
Utilizes the advanced wav2vec2.0-base architecture for fine-tuning.
Emotion Recognition Capability
Optimized specifically for speech emotion recognition tasks.

Model Capabilities

Speech Emotion Classification
Speech Feature Extraction
Emotional State Recognition

Use Cases

Mental Health Analysis
Depression Screening
Identifies potential depressive symptoms through speech analysis
Human-Computer Interaction
Smart Customer Service Emotion Recognition
Recognizes emotional states in user speech to provide more personalized services
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