Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Embedding-based subsequence matching with gaps-range-tolerances: a Query-By-Humming application
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Show others and affiliations
Number of Authors: 5
2015 (English)In: The VLDB journal, ISSN 1066-8888, E-ISSN 0949-877X, Vol. 24, no 4, 519-536 p.Article in journal (Refereed) Published
Abstract [en]

We present a subsequence matching framework that allows for gaps in both query and target sequences, employs variable matching tolerance efficiently tuned for each query and target sequence, and constrains the maximum matching range. Using this framework, a dynamic programming method is proposed, called SMBGT, that, given a short query sequence Q and a large database, identifies in quadratic time the subsequence of the database that best matches Q. SMBGT is highly applicable to music retrieval. However, in Query-By-Humming applications, runtime is critical. Hence, we propose a novel embedding-based approach, called ISMBGT, for speeding up search under SMBGT. Using a set of reference sequences, ISMBGT maps both Q and each position of each database sequence into vectors. The database vectors closest to the query vector are identified, and SMBGT is then applied between Q and the subsequences that correspond to those database vectors. The key novelties of ISMBGT are that it does not require training, it is query sensitive, and it exploits the flexibility of SMBGT. We present an extensive experimental evaluation using synthetic and hummed queries on a large music database. Our findings show that ISMBGT can achieve speedups of up to an order of magnitude against brute-force search and over an order of magnitude against cDTW, while maintaining a retrieval accuracy very close to that of brute-force search.

Place, publisher, year, edition, pages
2015. Vol. 24, no 4, 519-536 p.
Keyword [en]
Subsequence matching, Query-By-Humming, Indexing, Embeddings
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Information Systems
Identifiers
URN: urn:nbn:se:su:diva-119533DOI: 10.1007/s00778-015-0387-0ISI: 000358255800003OAI: oai:DiVA.org:su-119533DiVA: diva2:847835
Available from: 2015-08-21 Created: 2015-08-17 Last updated: 2015-08-21Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Karlsson, IsakPapapetrou, Panagiotis
By organisation
Department of Computer and Systems Sciences
In the same journal
The VLDB journal
Electrical Engineering, Electronic Engineering, Information EngineeringInformation Systems

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 29 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf