Local summarization and multi-level LSH for retrieving multi-variant audio tracks

Yi Yu, Michel Crucianu, Vincent Oria, Lei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

In this paper we study the problem of detecting and grouping multi-variant audio tracks in large audio datasets. To address this issue, a fast and reliable retrieval method is necessary. But reliability requires elaborate representations of audio content, which challenges fast retrieval by similarity from a large audio database. To find a better tradeoff between retrieval quality and efficiency, we put forward an approach relying on local summarization and multi-level Locality-Sensitive Hashing (LSH). More precisely, each audio track is divided into multiple Continuously Correlated Periods (CCP) of variable length according to spectral similarity. The description for each CCP is calculated based on its Weighted Mean Chroma (WMC). A track is thus represented as a sequence of WMCs. Then, an adapted two-level LSH is employed for efficiently delineating a narrow relevant search region. The "coarse" hashing level restricts search to items having a non-negligible similarity to the query. The subsequent, "refined" level only returns items showing a much higher similarity. Experimental evaluations performed on a real multi-variant audio dataset confirm that our approach supports fast and reliable retrieval of audio track variants.

Original languageEnglish (US)
Title of host publicationMM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums
Pages341-350
Number of pages10
DOIs
StatePublished - 2009
Event17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums - Beijing, China
Duration: Oct 19 2009Oct 24 2009

Publication series

NameMM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums

Other

Other17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums
Country/TerritoryChina
CityBeijing
Period10/19/0910/24/09

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software

Keywords

  • Local audio summarization
  • Multi-level LSH
  • Multi-variant musical audio search

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