Exploiting domain knowledge in music information research

Abstract

Music Information Research (MIR) is a discipline that aims to understand and model music from an information processing perspective, but the successful approaches used in MIR are going beyond the traditional data processing methodologies. Most of the great advancements have been the result of combining engineering disciplines such as audio signal processing and machine learning with non-engineering disciplines such as music perception and music theory. One of the challenges in MIR is to automatically describe music audio signals, thus to develop methodologies to extract musically useful information from audio recordings. In this paper we claim that if we want to advance in this direction we should maximize the use of musical knowledge in all the steps of our research tasks. To support this claim we overview some of the work being carried out in CompMusic, a project that aims to analyze and automatically describe the music of several non-western music traditions.