• Login
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    Towards joint sound scene and polyphonic sound event recognition 
    •   QMRO Home
    • School of Electronic Engineering and Computer Science
    • Centre for Digital Music (C4DM)
    • Towards joint sound scene and polyphonic sound event recognition
    •   QMRO Home
    • School of Electronic Engineering and Computer Science
    • Centre for Digital Music (C4DM)
    • Towards joint sound scene and polyphonic sound event recognition
    ‌
    ‌

    Browse

    All of QMROCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    ‌
    ‌

    Administrators only

    Login
    ‌
    ‌

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Towards joint sound scene and polyphonic sound event recognition

    View/Open
    Accepted version (212.4Kb)
    Pagination
    4594 - 4598
    Publisher
    International Speech Communication Association (ISCA)
    Publisher URL
    https://www.interspeech2019.org/
    Metadata
    Show full item record
    Abstract
    Acoustic Scene Classification (ASC) and Sound Event Detection (SED) are two separate tasks in the field of computational sound scene analysis. In this work, we present a new dataset with both sound scene and sound event labels and use this to demonstrate a novel method for jointly classifying sound scenes and recognizing sound events. We show that by taking a joint approach, learning is more efficient and whilst improvements are still needed for sound event detection, SED results are robust in a dataset where the sample distribution is skewed towards sound scenes.
    Authors
    Bear, H; Nolasco, I; Benetos, E; 20th Annual Conference of the International Speech Communication Association (INTERSPEECH 2019)
    URI
    https://qmro.qmul.ac.uk/xmlui/handle/123456789/58478
    Collections
    • Centre for Digital Music (C4DM) [210]
    Copyright statements
    © The Author(s) 2019
    Twitter iconFollow QMUL on Twitter
    Twitter iconFollow QM Research
    Online on twitter
    Facebook iconLike us on Facebook
    • Site Map
    • Privacy and cookies
    • Disclaimer
    • Accessibility
    • Contacts
    • Intranet
    • Current students

    Modern Slavery Statement

    Queen Mary University of London
    Mile End Road
    London E1 4NS
    Tel: +44 (0)20 7882 5555

    © Queen Mary University of London.