research-article

Modeling concept dynamics for large scale music search

Authors:

Shuicheng YanAuthors Info & Claims

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

Pages 455 - 464

https://doi.org/10.1145/2348283.2348346

Published: 12 August 2012 Publication History

Abstract

Continuing advances in data storage and communication technologies have led to an explosive growth in digital music collections. To cope with their increasing scale, we need effective Music Information Retrieval (MIR) capabilities like tagging, concept search and clustering. Integral to MIR is a framework for modelling music documents and generating discriminative signatures for them. In this paper, we introduce a multimodal, layered learning framework called DMCM. Distinguished from the existing approaches that encode music as an ensemble of order-less feature vectors, our framework extracts from each music document a variety of acoustic features, and translates them into low-level encodings over the temporal dimension. From them, DMCM elucidates the concept dynamics in the music document, representing them with a novel music signature scheme called Stochastic Music Concept Histogram (SMCH) that captures the probability distribution over all the concepts. Experiment results with two large music collections confirm the advantages of the proposed framework over existing methods on various MIR tasks.

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Cited By

Yang J(2022)Personalized Song Recommendation System Based on Vocal CharacteristicsMathematical Problems in Engineering10.1155/2022/36057282022(1-10)Online publication date: 16-Mar-2022
https://doi.org/10.1155/2022/3605728
Mor BGarhwal SKumar A(2021)MIMVOGUE: modeling Indian music using a variable order gapped HMMMultimedia Tools and Applications10.1007/s11042-020-10303-yOnline publication date: 30-Jan-2021
https://doi.org/10.1007/s11042-020-10303-y
Bayle YRobine MHanna P(2019)SATINMultimedia Tools and Applications10.1007/s11042-018-5797-878:3(2703-2718)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s11042-018-5797-8
Show More Cited By

Index Terms

Modeling concept dynamics for large scale music search
1. Applied computing
  1. Arts and humanities
    1. Sound and music computing
2. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Multimedia and multimodal retrieval
        Music retrieval

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Published In

cover image ACM Conferences

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

August 2012

1236 pages

ISBN:9781450314725

DOI:10.1145/2348283

General Chair:
William Hersh
Oregon Health & Science University, USA
,
Program Chairs:
Jamie Callan
Carnegie Mellon University, USA
,
Yoelle Maarek
Yahoo! Research, Israel
,
Mark Sanderson
Royal Melbourne Institute of Technology, Australia

Copyright © 2012 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: 12 August 2012

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SIGIR '12

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SIGIR

SIGIR '12: The 35th International ACM SIGIR conference on research and development in Information Retrieval

August 12 - 16, 2012

Oregon, Portland, USA

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

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Cited By

Yang J(2022)Personalized Song Recommendation System Based on Vocal CharacteristicsMathematical Problems in Engineering10.1155/2022/36057282022(1-10)Online publication date: 16-Mar-2022
https://doi.org/10.1155/2022/3605728
Mor BGarhwal SKumar A(2021)MIMVOGUE: modeling Indian music using a variable order gapped HMMMultimedia Tools and Applications10.1007/s11042-020-10303-yOnline publication date: 30-Jan-2021
https://doi.org/10.1007/s11042-020-10303-y
Bayle YRobine MHanna P(2019)SATINMultimedia Tools and Applications10.1007/s11042-018-5797-878:3(2703-2718)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s11042-018-5797-8
Cheng ZShen JZhu LKankanhalli MNie L(2017)Exploiting music play sequence for music recommendationProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3172077.3172400(3654-3660)Online publication date: 19-Aug-2017
https://dl.acm.org/doi/10.5555/3172077.3172400
Cheng ZShen JNie LChua TKankanhalli MKando NSakai TJoho HLi Hde Vries AWhite R(2017)Exploring User-Specific Information in Music RetrievalProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080772(655-664)Online publication date: 7-Aug-2017
https://dl.acm.org/doi/10.1145/3077136.3080772
Hendry Chen RLiu L(2017)A Personalized Recommendation Method Considering Local and Global InfluencesIntelligent Information and Database Systems10.1007/978-3-319-54472-4_62(663-672)Online publication date: 26-Feb-2017
https://doi.org/10.1007/978-3-319-54472-4_62
Cheng ZJialie SHoi SPerego RSebastiani FAslam JRuthven IZobel J(2016)On Effective Personalized Music Retrieval by Exploring Online User BehaviorsProceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval10.1145/2911451.2911491(125-134)Online publication date: 7-Jul-2016
https://dl.acm.org/doi/10.1145/2911451.2911491
Baniya BLee J(2016)Importance of audio feature reduction in automatic music genre classificationMultimedia Tools and Applications10.1007/s11042-014-2418-z75:6(3013-3026)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1007/s11042-014-2418-z
Cheng ZShen JBaeza-Yates RLalmas MMoffat ARibeiro-Neto B(2015)VenueMusicProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/2766462.2767869(1029-1030)Online publication date: 9-Aug-2015
https://dl.acm.org/doi/10.1145/2766462.2767869
Zhang PZheng XZhang WLi SQian SHe WZhang SWang ZHauptmann ANgo CXue XJiang YSnoek CVasconcelos N(2015)A Deep Neural Network for Modeling MusicProceedings of the 5th ACM on International Conference on Multimedia Retrieval10.1145/2671188.2749367(379-386)Online publication date: 22-Jun-2015
https://dl.acm.org/doi/10.1145/2671188.2749367
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