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Randomly Sketched Sparse Subspace Clustering for Acoustic Scene Clustering

Li, Shuoyang and Wang, Wenwu (2018) Randomly Sketched Sparse Subspace Clustering for Acoustic Scene Clustering In: 26th European Signal Processing Conference, 3 - 7 September 2018, Rome, Italy.

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Abstract

Acoustic scene classification has drawn much research attention where labeled data are often used for model training. However, in practice, acoustic data are often unlabeled, weakly labeled, or incorrectly labeled. To classify unlabeled data, or detect and correct wrongly labeled data, we present an unsupervised clustering method based on sparse subspace clustering. The computational cost of the sparse subspace clustering algorithm becomes prohibitively high when dealing with high dimensional acoustic features. To address this problem, we introduce a random sketching method to reduce the feature dimensionality for the sparse subspace clustering algorithm. Experimental results reveal that this method can reduce the computational cost significantly with a limited loss in clustering accuracy.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Li, Shuoyangshuoyang.li@surrey.ac.uk
Wang, WenwuW.Wang@surrey.ac.uk
Date : 2018
Copyright Disclaimer : © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Melanie Hughes
Date Deposited : 26 Sep 2018 11:51
Last Modified : 26 Sep 2018 11:52
URI: http://epubs.surrey.ac.uk/id/eprint/849445

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