The Audio-Visual Arabic Dataset for Natural Emotions

Abstract

Emotions are a crucial aspect of human life and the researchers have tried to build an automatic emotion recognition system that helps to provide important real-world applications. The psychologists have shown that emotions differ across culture, considering this fact, we provide and describe the first audio-visual Arabic emotional dataset which called (AVANEmo). In this work we aim to fill the gap between studies of emotion recognition for Arabic content and other languages by provided an Arabic dataset which is a major and fundamental part of build emotion recognition application. Our dataset contains 3000 clips for video and audio data, and it covers six basic emotional labels (Happy, Sad, Angry, Surprise, Disgust, Neutral). Also, we provide some baseline experiments to measure the primitive performance for automated audio and visual emotion recognition application using the AVANEmo dataset. The best accuracy that we achieved was 54.5% and 57.9% using the audio and visual data respectively. The data will be available for distribution to researchers.