skip to main content
10.1145/964696.964700acmconferencesArticle/Chapter ViewAbstractPublication PagesuistConference Proceedingsconference-collections
Article

SmartMusicKIOSK: music listening station with chorus-search function

Authors Info & Claims
Published:02 November 2003Publication History

ABSTRACT

This paper describes a new music-playback interface for trial listening, SmartMusicKIOSK. In music stores, short trial listening of CD music is not usually a passive experience -- customers often search out the chorus or "hook" of a song using the fast-forward button. Listening of this type, however, has not been traditionally supported. This research achieves a function for jumping to the chorus section and other key parts of a song plus a function for visualizing song structure. These functions make it easier for a listener to find desired parts of a song and thereby facilitate an active listening experience. The proposed functions are achieved by an automatic chorus-section detecting method, and the results of implementing them as a listening station have demonstrated their usefulness.

Skip Supplemental Material Section

Supplemental Material

p31-goto_512k.mov

mov

26.4 MB

p31-goto_56k.mov

mov

2.1 MB

p31-goto_768k.mov

mov

41.8 MB

References

  1. 1. Mark A. Bartsch and Gregory H. Wakefield. To catch a chorus: Using chroma-based representations for audio thumbnailing. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA'01), pages 15-18, 2001.]]Google ScholarGoogle Scholar
  2. 2. Matthew Cooper and Jonathan Foote. Automatic music summarization via similarity analysis. In Proc. of ISMIR 2002, pages 81-85, 2002.]]Google ScholarGoogle Scholar
  3. 3. Roger Dannenberg. Music understanding by computer. In IAKTA/LIST International Workshop on Knowledge Technology in the Arts Proc., pages 41-56, 1993.]]Google ScholarGoogle Scholar
  4. 4. Roger B. Dannenberg and Ning Hu. Pattern discovery techniques for music audio. In Proc. of ISMIR 2002, pages 63-70, 2002.]]Google ScholarGoogle Scholar
  5. 5. Peter Desain and Henkjan Honing. Music, Mind and Machine: Studies in Computer Music, Music Cognition and Artificial Intelligence. Thesis Publishers, 1992.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. 6. Masataka Goto. A robust predominant-F0 estimation method for real-time detection of melody and bass lines in CD recordings. In Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2000), pages II-757-760, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. 7. Masataka Goto. An audio-based real-time beat tracking system for music with or without drum-sounds. J. of New Music Research, 30(2):159-171, 2001.]]Google ScholarGoogle ScholarCross RefCross Ref
  8. 8. Masataka Goto. Music scene description: Toward audio-based real-time music understanding. J. Acoust. Soc. Am., 111(5, Pt.2):2349, 2002. (Invited Paper of the 143rd Meeting of the Acoustical Society of America).]]Google ScholarGoogle Scholar
  9. 9. Masataka Goto, Hiroki Hashiguchi, Takuichi Nishimura, and Ryuichi Oka. RWC music database: Popular, classical, and jazz music databases. In Proc. of ISMIR 2002, pages 287-288, 2002.]]Google ScholarGoogle Scholar
  10. 10. Masataka Goto and Yoichi Muraoka. A beat tracking system for acoustic signals of music. In Proc. of ACM Multimedia 94, pages 365-372, 1994.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. 11. Masataka Goto, Ryo Neyama, and Yoichi Muraoka. RMCP: Remote music control protocol -- design and applications --. In Proc. of Intl. Computer Music Conf., pages 446-449, 1997.]]Google ScholarGoogle Scholar
  12. 12. Rumi Hiraga. Case study: A look of performance expression. In Proc. of IEEE Visualization 2002, pages 501-504, 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. 13. Rumi Hiraga, Shigeru Igarashi, and Yohei Matsuura. Visualized music expression in an object-oriented environment. In Proc. of Intl. Computer Music Conf., pages 483-486, 1996.]]Google ScholarGoogle Scholar
  14. 14. Rumi Hiraga, Reiko Miyazaki, and Issei Fujishiro. Performance visualization - a new challenge to music through visualization. In Proc. of ACM Multimedia 2002, pages 239-242, 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. 15. Keiji Hirata and Shu Matsuda. Interactive music summarization based on GTTM. In Proc. of ISMIR 2002, pages 86-93, 2002.]]Google ScholarGoogle Scholar
  16. 16. Proc. of International Symposium on Music Information Retrieval (ISMIR 2000), 2000.]]Google ScholarGoogle Scholar
  17. 17. Proc. of International Symposium on Music Information Retrieval (ISMIR 2001), 2001.]]Google ScholarGoogle Scholar
  18. 18. Proc. of International Conference on Music Information Retrieval (ISMIR 2002), 2002.]]Google ScholarGoogle Scholar
  19. 19. Beth Logan and Stephen Chu. Music summarization using key phrases. In Proc. of ICASSP 2000, pages II- 749-752, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. 20. Nobuyuki Otsu. A threshold selection method from gray-level histograms. IEEE Trans. SMC, SMC- 9(1):62-66, 1979.]]Google ScholarGoogle ScholarCross RefCross Ref
  21. 21. Geoffroy Peeters, Amaury La Burthe, and Xavier Rodet. Toward automatic music audio summary generation from signal analysis. In Proc. of ISMIR 2002, pages 94-100, 2002.]]Google ScholarGoogle Scholar
  22. 22. Robert Rowe. Machine Musicianship. The MIT Press, 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. 23. Roger N. Shepard. Circularity in judgments of relative pitch. J. Acoust. Soc. Am., 36(12):2346-2353, 1964.]]Google ScholarGoogle ScholarCross RefCross Ref
  24. 24. Sean M. Smith and Glen N. Williams. A visualization of music. In Proc. of IEEE Visualization '97, pages 499-503, 1997.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. 25. Tomonari Sonoda, Masataka Goto, and Yoichi Muraoka. A WWW-based melody retrieval system. In Proc. of Intl. Computer Music Conf., pages 349-352, 1998.]]Google ScholarGoogle Scholar
  26. 26. C. J. van Rijsbergen. Information Retrieval. Butterworths, second edition, 1979.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. 27. Gerhard Widmer. In search of the horowitz factor: Interim report on a musical discovery project. In Proc. of International Conference on Discovery Science (DS 2002), pages 13-21, 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. SmartMusicKIOSK: music listening station with chorus-search function

                Recommendations

                Comments

                Login options

                Check if you have access through your login credentials or your institution to get full access on this article.

                Sign in
                • Published in

                  cover image ACM Conferences
                  UIST '03: Proceedings of the 16th annual ACM symposium on User interface software and technology
                  November 2003
                  220 pages
                  ISBN:1581136366
                  DOI:10.1145/964696

                  Copyright © 2003 ACM

                  Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                  Publisher

                  Association for Computing Machinery

                  New York, NY, United States

                  Publication History

                  • Published: 2 November 2003

                  Permissions

                  Request permissions about this article.

                  Request Permissions

                  Check for updates

                  Qualifiers

                  • Article

                  Acceptance Rates

                  UIST '03 Paper Acceptance Rate25of116submissions,22%Overall Acceptance Rate842of3,967submissions,21%

                  Upcoming Conference

                  UIST '24

                PDF Format

                View or Download as a PDF file.

                PDF

                eReader

                View online with eReader.

                eReader