IIITSaint-EmoMDB: Carefully Curated Malayalam Speech Corpus with Emotion and Self-Reported Depression Ratings

Mental health conditions such as depression and anxiety are pervasive issues that affect millions of individuals worldwide. Understanding the intricate relationship between emotional perception and mental health is crucial. This work develops a database named IIITSaint-EmoMDB containing Malayalam language speech samples annotated with emotion ratings at valence and arousal scale using three annotators considering four emotion labels: happy, sad, angry and neutral. In addition to emotion ratings, emotional perception is rated from 150 participants according to the circumplex model of va-lence and arousal. The database also consists of self-reported mental health scores of those participants based on PHQ-9 and GAD-7 questionnaire. Our preliminary analysis of comparing the participants' emotional perception based PHQ-9 and GAD-7 scores revealed that the depressed category showed the highest deviation from the emotion perception of people compared to the mild depression and non-depression categories.