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

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.

Audio Cover Song Identification and Similarity: Background, Approaches, Evaluation, and Beyond

“…Nowadays, online digital music collections are in the order of ten [59] to a few hundred million tracks 2 and they are continuously increasing. Therefore, one can hypothesize that the ability to manage this huge amount of digital information in an efficient and reliable way will make the difference in tomorrow's music-related industry [10,85]. Personal music collections, which by now can easily exceed the practical limits on the time to listen to them, might benefit as well from efficient and reliable search and retrieval engines.…”

Pitch-frequency histogram-based music information retrieval for Turkish music

“…Although Music Information Retrieval (MIR) on western music has become a well-established research domain (for a comprehensive state-of-art on MIR, see [2]), its applications on non-western musics are still very limited. Although there are a large number of nonwestern performers, listeners and a long history of nonwestern musics, the MIR research for non-western musics is in its early stages (a comprehensive review of ''computational ethnomusicology'' is presented in [3]).…”

Indexing music by mood: design and integration of an automatic content-based annotator

“…In the past few years, research in content-based techniques has been trying to solve the problem of tedious and time-consuming human indexing of audiovisual data. In particular, Music Information Retrieval (MIR) has been very active in a wide variety of topics such as automatic transcription or genre classification [5,29,41]. Recently, classification of music mood has become a matter of interest, mainly because of the close relationship between music and emotions [1,20].…”