Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
Towards the digital music library: tune retrieval from acoustic input
Proceedings of the first ACM international conference on Digital libraries
A tool for content based navigation of music
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Musical content-based retrieval: an overview of the Melodiscov approach and system
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Tune Retrieval in the Multimedia Library
Multimedia Tools and Applications
A statistical approach to retrieval under user-dependent uncertainty in query-by-humming systems
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Proceedings of the 1st ACM workshop on Audio and music computing multimedia
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Advances in music retrieval research greatly depend on appropriate database resources and their meaningful organization. In this paper we describe the data collection efforts related to the design of query by humming (QBH) systems. We also provide a statistical analysis for categorizing the collected data, especially focusing on inter-subject variability issues. In total, 100 people participated in our experiment resulting in around 2000 humming samples drown from a predefined melody list consisting of 22 different well known music pieces, and over 500 samples of melodies that were chosen spontaneously by our subjects. These data will be made available for the research community. The data from each subject were compared to the expected melody features, and an objective measure was derived to quantify the statistical deviation from the baseline. The results showed that the uncertainty in the humming varies with respect to the melodies' musical structure and subjects' musical background. Such details are important for designing robust QBH systems.