AI

The Need for Music Information Retrieval with User-Centered and Multimodal Strategies

Abstract

Music is a widely enjoyed content type, existing in many multifaceted representations. With the digital information age, a lot of digitized music information has theoretically become available at the user’s fingertips. However, the abundance of information is too large-scaled and too diverse to annotate, oversee and present in a consistent and human manner, motivating the development of automated Music Information Retrieval (Music-IR) techniques.

In this paper, we encourage to consider music content beyond a monomodal audio signal and argue that Music-IR approaches with multimodal and user-centered strategies are necessary to serve reallife usage patterns and maintain and improve accessibility of digital music data. After discussing relevant existing work in these directions, we show that the field of Music-IR faces similar challenges as neighboring fields, and thus suggest opportunities for joint collaboration and mutual inspiration.