Building a music search database using human computation

Mark Cartwright, Bryan A Pardo

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

Abstract

Systems able to find a song based on a sung, hummed, or whistled melody are called Query-By-Humming (QBH) systems. Hummed or sung queries are not directly compared to original recordings. Instead, systems employ search keys that are more similar to a cappella singing than the original pieces. Successful, deployed systems use human computation to create search keys: hand-entered midi melodies or recordings of a cappella singing. There are a number of human computation-based approaches that may be used to build a database of QBH search keys, but it is not clear what the best choice is based on cost, computation time, and search performance. In this paper we compare search keys built through human computation using two populations: paid local singers and Amazon Mechanical Turk workers. We evaluate them on quality, cost, computation time, and search performance.

Original languageEnglish (US)
Title of host publicationProceedings of the 9th Sound and Music Computing Conference, SMC 2012
PublisherSound and music Computing network
ISBN (Print)9783832531805
StatePublished - 2012
Event9th Sound and Music Computing Conference, SMC 2012 - Copenhagen, Denmark
Duration: Jul 11 2012Jul 14 2012

Publication series

NameProceedings of the 9th Sound and Music Computing Conference, SMC 2012

Other

Other9th Sound and Music Computing Conference, SMC 2012
CountryDenmark
CityCopenhagen
Period7/11/127/14/12

ASJC Scopus subject areas

  • Computer Science(all)

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