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Urdu Audio Emotions

Developed by Talha
A fine-tuned Urdu audio emotion classification model based on facebook/wav2vec2-large-xlsr-53, supporting recognition of four emotions: anger, happiness, calmness, and sadness.
Downloads 66
Release Time : 7/2/2022

Model Overview

This model is designed for Urdu audio data emotion classification, capable of accurately identifying four emotional states in audio: anger, happiness, calmness, and sadness.

Model Features

High Accuracy
Achieves 97.5% classification accuracy on the evaluation set.
Multi-emotion Recognition
Can identify four emotional states: anger, happiness, calmness, and sadness.
Transfer Learning
Fine-tuned based on the pre-trained wav2vec2-large-xlsr-53 model.

Model Capabilities

Urdu Audio Processing
Emotion Classification
Speech Feature Extraction

Use Cases

Sentiment Analysis
Customer Service Call Analysis
Analyze customer emotional states in service calls.
Accurately identifies customer anger to improve service quality.
Mental Health Assessment
Assess user psychological state through voice analysis.
Identifies vocal features indicative of depressive tendencies.
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