Cross-cultural mood regression for music digital libraries

Abstract

Mood is a popular access point in music digital libraries and online music repositories, and is often represented as numerical values in a small number of emotion-related dimensions (e.g., valence and arousal). As music mood is recognized as culturally dependent, this study investigates whether regression models built with music data in one culture can be applied to music in another culture. Results indicate that cross-cultural predictions of both valence and arousal values are feasible.