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Acoustic Scene Classification: A Competition Review

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

Details

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

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.

Publication forum classification

Field of science, Statistics Finland