Landmark-based Audio Fingerprinting for DJ Mix Monitoring.

Description

Recently, the media monitoring industry shows increased interest in applying automated audio identification systems for revenue distribution of DJ performances played in dis- cotheques. DJ mixes incorporate a wide variety of signal modifications, e.g. pitch shifting, tempo modifications, cross-fading and beat-matching. These signal modifica- tions are expected to be more severe than what is usually encountered in the monitoring of radio and TV broadcasts. The monitoring of DJ mixes presents a hard challenge for automated music identification systems, which need to be robust to various signal modifications while maintaining a high level of specificity to avoid false revenue assignment. In this work we assess the fitness of three landmark-based audio fingerprinting systems with different properties on real-world data – DJ mixes that were performed in dis- cotheques. To enable the research community to evaluate systems on DJ mixes, we also create and publish a freely available, creative-commons licensed dataset of DJ mixes along with their reference tracks and song-border annota- tions. Experiments on these datasets reveal that a recent quad-based method achieves considerably higher perfor- mance on this task than the other methods.

Period	08 Aug 2016
Event title	17th International Society for Music Information Retrieval Conference (ISMIR 2016),
Event type	Other
Location	New York, United States, New YorkShow on map