Acoustic Scene Classification: A Competition Review

Shayan Gharib, Honain Derrar, Daisuke Niizumi, Tuukka Senttula, Janne Tommola, Toni Heittola, Tuomas Virtanen, Heikki Huttunen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    5 Citations (Scopus)

    Abstract

    In this paper we study the problem of acoustic scene classification, i.e., categorization of audio sequences into mutually exclusive classes based on their spectral content. We describe the methods and results discovered during a competition organized in the context of a graduate machine learning course; both by the students and external participants. We identify the most suitable methods and study the impact of each by performing an ablation study of the mixture of approaches. We also compare the results with a neural network baseline, and show the improvement over that. Finally, we discuss the impact of using a competition as a part of a university course, and justify its importance in the curriculum based on student feedback.
    Original languageEnglish
    Title of host publication2018 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2018
    PublisherIEEE
    ISBN (Electronic)9781538654774
    DOIs
    Publication statusPublished - Sep 2018
    Publication typeA4 Article in a conference publication
    EventIEEE International Workshop on Machine Learning for Signal Processing -
    Duration: 17 Sep 201820 Sep 2018

    Conference

    ConferenceIEEE International Workshop on Machine Learning for Signal Processing
    Period17/09/1820/09/18

    Publication forum classification

    • Publication forum level 1

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