Content-Based Music Information Retrieval: Current Directions and Future Challenges

TLDR

The music industry’s shift from CD sales to online streaming and downloads has produced massive digital libraries of up to ten million tracks, creating a pressing need for efficient search, retrieval, and organization of music content. This paper aims to outline the challenges of content‑based music information retrieval and to survey current state‑of‑the‑art methods. It reviews audio‑cue techniques such as query‑by‑humming, audio fingerprinting, and content‑based retrieval, as well as symbolic‑cue approaches using music notation.

Abstract

The steep rise in music downloading over CD sales has created a major shift in the music industry away from physical media formats and towards online products and services. Music is one of the most popular types of online information and there are now hundreds of music streaming and download services operating on the World-Wide Web. Some of the music collections available are approaching the scale of ten million tracks and this has posed a major challenge for searching, retrieving, and organizing music content. Research efforts in music information retrieval have involved experts from music perception, cognition, musicology, engineering, and computer science engaged in truly interdisciplinary activity that has resulted in many proposed algorithmic and methodological solutions to music search using content-based methods. This paper outlines the problems of content-based music information retrieval and explores the state-of-the-art methods using audio cues (e.g., query by humming, audio fingerprinting, content-based music retrieval) and other cues (e.g., music notation and symbolic representation), and identifies some of the major challenges for the coming years.