Landmark-based Audio Fingerprinting for DJ Mix Monitoring.
Sprache des Vortragstitels:
17th International Society for Music Information Retrieval Conference (ISMIR)
Sprache des Tagungstitel:
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.