An adaptation framework for QBH-based music retrieval

Seungmin Rho; Byeong Jun Han; Eenjun Hwang; Minkoo Kim

doi:10.1007/978-3-540-74819-9_74

An adaptation framework for QBH-based music retrieval

Seungmin Rho, Byeong Jun Han, Eenjun Hwang, Minkoo Kim

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In this paper, we present a new music query transcription and refinement scheme for efficient music retrieval. For the accurate music query transcription into symbolic representation, we propose a method called WAE for note onset detection, and DTC for ADF onset detection. Also, in order to improve the retrieval performance, we propose a new relevance feedback scheme using genetic algorithm. We have built a prototype system based on this scheme and performed various experiments. Experimental results show that our proposed scheme achieves a good performance.

Original language	English
Title of host publication	Knowledge-Based Intelligent Information and Engineering Systems
Subtitle of host publication	KES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings
Publisher	Springer Verlag
Pages	596-603
Number of pages	8
Edition	PART 1
ISBN (Print)	9783540748175
DOIs	https://doi.org/10.1007/978-3-540-74819-9_74
Publication status	Published - 2007
Event	11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 - Vietri sul Mare, Italy Duration: 2007 Sept 12 → 2007 Sept 14

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	4692 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007
Country/Territory	Italy
City	Vietri sul Mare
Period	07/9/12 → 07/9/14

Keywords

Genetic algorithm
Music retrieval
Relevance feedback

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-74819-9_74

Cite this

Rho, S., Han, B. J., Hwang, E., & Kim, M. (2007). An adaptation framework for QBH-based music retrieval. In Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings (PART 1 ed., pp. 596-603). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4692 LNAI, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-74819-9_74

An adaptation framework for QBH-based music retrieval. / Rho, Seungmin; Han, Byeong Jun; Hwang, Eenjun et al.
Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings. PART 1. ed. Springer Verlag, 2007. p. 596-603 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4692 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Rho, S, Han, BJ, Hwang, E & Kim, M 2007, An adaptation framework for QBH-based music retrieval. in Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4692 LNAI, Springer Verlag, pp. 596-603, 11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007, Vietri sul Mare, Italy, 07/9/12. https://doi.org/10.1007/978-3-540-74819-9_74

Rho S, Han BJ, Hwang E, Kim M. An adaptation framework for QBH-based music retrieval. In Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings. PART 1 ed. Springer Verlag. 2007. p. 596-603. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-74819-9_74

Rho, Seungmin ; Han, Byeong Jun ; Hwang, Eenjun et al. / An adaptation framework for QBH-based music retrieval. Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings. PART 1. ed. Springer Verlag, 2007. pp. 596-603 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{595a1c82c68b4e3eaede3b94e936af4b,

title = "An adaptation framework for QBH-based music retrieval",

abstract = "In this paper, we present a new music query transcription and refinement scheme for efficient music retrieval. For the accurate music query transcription into symbolic representation, we propose a method called WAE for note onset detection, and DTC for ADF onset detection. Also, in order to improve the retrieval performance, we propose a new relevance feedback scheme using genetic algorithm. We have built a prototype system based on this scheme and performed various experiments. Experimental results show that our proposed scheme achieves a good performance.",

keywords = "Genetic algorithm, Music retrieval, Relevance feedback",

author = "Seungmin Rho and Han, {Byeong Jun} and Eenjun Hwang and Minkoo Kim",

year = "2007",

doi = "10.1007/978-3-540-74819-9_74",

language = "English",

isbn = "9783540748175",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

number = "PART 1",

pages = "596--603",

booktitle = "Knowledge-Based Intelligent Information and Engineering Systems",

edition = "PART 1",

note = "11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 ; Conference date: 12-09-2007 Through 14-09-2007",

}

TY - GEN

T1 - An adaptation framework for QBH-based music retrieval

AU - Rho, Seungmin

AU - Han, Byeong Jun

AU - Hwang, Eenjun

AU - Kim, Minkoo

PY - 2007

Y1 - 2007

N2 - In this paper, we present a new music query transcription and refinement scheme for efficient music retrieval. For the accurate music query transcription into symbolic representation, we propose a method called WAE for note onset detection, and DTC for ADF onset detection. Also, in order to improve the retrieval performance, we propose a new relevance feedback scheme using genetic algorithm. We have built a prototype system based on this scheme and performed various experiments. Experimental results show that our proposed scheme achieves a good performance.

AB - In this paper, we present a new music query transcription and refinement scheme for efficient music retrieval. For the accurate music query transcription into symbolic representation, we propose a method called WAE for note onset detection, and DTC for ADF onset detection. Also, in order to improve the retrieval performance, we propose a new relevance feedback scheme using genetic algorithm. We have built a prototype system based on this scheme and performed various experiments. Experimental results show that our proposed scheme achieves a good performance.

KW - Genetic algorithm

KW - Music retrieval

KW - Relevance feedback

UR - http://www.scopus.com/inward/record.url?scp=38149006997&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-74819-9_74

DO - 10.1007/978-3-540-74819-9_74

M3 - Conference contribution

AN - SCOPUS:38149006997

SN - 9783540748175

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 596

EP - 603

BT - Knowledge-Based Intelligent Information and Engineering Systems

PB - Springer Verlag

T2 - 11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007

Y2 - 12 September 2007 through 14 September 2007

ER -

An adaptation framework for QBH-based music retrieval

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this