MU Face Emotion - Building a Large Dataset for Emotional Facial Expression in Psychological Domain

Abstract

Currently, several well-known facial datasets have been proposed and used to train artificial intelligence models for facial expression interpretation. However, since each dataset varies in terms of ethnicity and facial expression characteristics, using the currently available dataset does not yield satisfactory results in predicting the emotional expressions of Thai people. As a result, the research team has developed a dataset on the facial expressions of Thai people, which may be used by academics to study and improve-facial expression analysis research. There were two different kinds of datasets created by the research team: audio datasets and image datasets. The research team created two kinds of datasets: audio datasets and image datasets, each of which includes five classes: positive-active (happy), positive-deactivate (relaxed), neutral, negative-active (anger, stress), and negative-deactivate (sad). This dataset was created using data from 24 volunteers who were analyzed for their emotional expression by a group of psychologists from Mahidol University using standardized procedures. The research team calls this information MU-Corpus.