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dc.contributor.authorTian, Mi
dc.date.accessioned2017-07-07T13:30:05Z
dc.date.available2017-07-07T13:30:05Z
dc.date.issued2017-10-01
dc.date.submitted2017-07-07T13:45:02.047Z
dc.identifier.citationTian, M. 2017. A Cross-Cultural Analysis of Music Structure. Queen Mary University of Londonen_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/24782
dc.descriptionPhDen_US
dc.description.abstractMusic signal analysis is a research field concerning the extraction of meaningful information from musical audio signals. This thesis analyses the music signals from the note-level to the song-level in a bottom-up manner and situates the research in two Music information retrieval (MIR) problems: audio onset detection (AOD) and music structural segmentation (MSS). Most MIR tools are developed for and evaluated on Western music with specific musical knowledge encoded. This thesis approaches the investigated tasks from a cross-cultural perspective by developing audio features and algorithms applicable for both Western and non-Western genres. Two Chinese Jingju databases are collected to facilitate respectively the AOD and MSS tasks investigated. New features and algorithms for AOD are presented relying on fusion techniques. We show that fusion can significantly improve the performance of the constituent baseline AOD algorithms. A large-scale parameter analysis is carried out to identify the relations between system configurations and the musical properties of different music types. Novel audio features are developed to summarise music timbre, harmony and rhythm for its structural description. The new features serve as effective alternatives to commonly used ones, showing comparable performance on existing datasets, and surpass them on the Jingju dataset. A new segmentation algorithm is presented which effectively captures the structural characteristics of Jingju. By evaluating the presented audio features and different segmentation algorithms incorporating different structural principles for the investigated music types, this thesis also identifies the underlying relations between audio features, segmentation methods and music genres in the scenario of music structural analysis.en_US
dc.description.sponsorshipChina Scholarship Council EPSRC C4DM Travel Funding, EPSRC Fusing Semantic and Audio Technologies for Intelligent Music Production and Consumption (EP/L019981/1), EPSRC Platform Grant on Digital Music (EP/K009559/1), European Research Council project CompMusic, International Society for Music Information Retrieval Student Grant, QMUL Postgraduate Research Fund, QMUL-BUPT Joint Programme Funding Women in Music Information Retrieval Grant.en_US
dc.language.isoenen_US
dc.publisherQueen Mary University of Londonen_US
dc.rightsThe copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author
dc.subjectElectronic engineering and computer scienceen_US
dc.subjectMusic signal analysisen_US
dc.subjectaudio onset detectionen_US
dc.subjectmusic structural segmentationen_US
dc.subjectC4DMen_US
dc.titleA Cross-Cultural Analysis of Music Structureen_US
dc.typeThesisen_US


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    Theses Awarded by Queen Mary University of London

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