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M-MUSICS: an intelligent mobile music retrieval system

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Abstract

Accurate voice humming transcription and efficient indexing and retrieval schemes are essential to a large-scale humming-based audio retrieval system. Although much research has been done to develop such schemes, their performance in terms of precision, recall, and F-measure, among all similarity metrics, are still unsatisfactory. In this paper, we propose a new voice query transcription scheme. It considers the following features: note onset detection using dynamic threshold methods, fundamental frequency (F0) acquisition of each frame, and frequency realignment using K-means. We use a popularity-adaptive indexing structure called frequently accessed index (FAI) based on frequently queried tunes for indexing purposes. In addition, we propose a semi-supervised relevance feedback and query reformulation scheme based on a genetic algorithm to improve retrieval efficiency. In this paper, we extend our efforts to mobile multimedia environments and develop a mobile audio retrieval system. Experiments show our system performs satisfactory in wireless mobile multimedia environments.

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Acknowledgments

“This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency)” (NIPA-2010-C1090-1031-0004). “This research was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0025395)”. We would like to specially thank to Byeong-jun Han who were dedicated as much as we were in this paper.

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Correspondence to Jong Hyuk Park.

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Rho, S., Hwang, E. & Park, J.H. M-MUSICS: an intelligent mobile music retrieval system. Multimedia Systems 17, 313–326 (2011). https://doi.org/10.1007/s00530-010-0212-y

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