research-article

Competence-based song recommendation

Authors:

Tianlei HuAuthors Info & Claims

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

Pages 423 - 432

https://doi.org/10.1145/2484028.2484048

Published: 28 July 2013 Publication History

Abstract

Singing is a popular social activity and a good way of expressing one's feelings. One important reason for unsuccessful singing performance is because the singer fails to choose a suitable song. In this paper, we propose a novel singing competence-based song recommendation framework. It is distinguished from most existing music recommendation systems which rely on the computation of listeners' interests or similarity. We model a singer's vocal competence as singer profile, which takes voice pitch, intensity, and quality into consideration. Then we propose techniques to acquire singer profiles. We also present a song profile model which is used to construct a human annotated song database. Finally, we propose a learning-to-rank scheme for recommending songs by singer profile. The experimental study on real singers demonstrates the effectiveness of our approach and its advantages over two baseline methods. To the best of our knowledge, our work is the first to study competence-based song recommendation.

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Cited By

Mao KChen GHu YZhang L(2016)Music recommendation using graph based quality modelSignal Processing10.1016/j.sigpro.2015.03.026120:C(806-813)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1016/j.sigpro.2015.03.026
Mao KShou LFan JChen GKankanhalli M(2015)Competence-Based Song Recommendation: Matching Songs to One’s Singing SkillIEEE Transactions on Multimedia10.1109/TMM.2015.239256217:3(396-408)Online publication date: Mar-2015
https://doi.org/10.1109/TMM.2015.2392562
Ji KSun RShu WLi X(2015)Next-song recommendation with temporal dynamicsKnowledge-Based Systems10.1016/j.knosys.2015.07.03988:C(134-143)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1016/j.knosys.2015.07.039
Show More Cited By

Index Terms

Competence-based song recommendation
1. Applied computing
  1. Arts and humanities
    1. Sound and music computing
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Published In

cover image ACM Conferences

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

July 2013

1188 pages

ISBN:9781450320344

DOI:10.1145/2484028

General Chairs:
Gareth J.F. Jones
Dublin City University, Ireland
,
Páraic Sheridan
Dublin City University, Ireland
,
Program Chairs:
Diane Kelly
University of North Carolina, Chapel Hill, USA
,
Maarten de Rijke
University of Amsterdam, The Netherlands
,
Tetsuya Sakai
Microsoft Research Asia, China

Copyright © 2013 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]

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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 July 2013

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SIGIR '13

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SIGIR

SIGIR '13: The 36th International ACM SIGIR conference on research and development in Information Retrieval

July 28 - August 1, 2013

Dublin, Ireland

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SIGIR '13 Paper Acceptance Rate 73 of 366 submissions, 20%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Mao KChen GHu YZhang L(2016)Music recommendation using graph based quality modelSignal Processing10.1016/j.sigpro.2015.03.026120:C(806-813)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1016/j.sigpro.2015.03.026
Mao KShou LFan JChen GKankanhalli M(2015)Competence-Based Song Recommendation: Matching Songs to One’s Singing SkillIEEE Transactions on Multimedia10.1109/TMM.2015.239256217:3(396-408)Online publication date: Mar-2015
https://doi.org/10.1109/TMM.2015.2392562
Ji KSun RShu WLi X(2015)Next-song recommendation with temporal dynamicsKnowledge-Based Systems10.1016/j.knosys.2015.07.03988:C(134-143)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1016/j.knosys.2015.07.039
Mao KFan JShou LChen GKankanhalli MHua KRui YSteinmetz RHanjalic ANatsev AZhu W(2014)Song Recommendation for Social Singing CommunityProceedings of the 22nd ACM international conference on Multimedia10.1145/2647868.2654921(127-136)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2647868.2654921

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