University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Coupled Sparse NMF vs. Random Forest Classification for Real Life Acoustic Event Detection

Sobieraj, Iwona and Plumbley, Mark (2016) Coupled Sparse NMF vs. Random Forest Classification for Real Life Acoustic Event Detection In: Detection and Classification of Acoustic Scenes and Events 2016, 3 Sept 2016, Budapest, Hungary.

[img]
Preview
Text
DCASE2016_SobierajIwona.pdf - Version of Record
Available under License : See the attached licence file.

Download (155kB) | Preview
[img]
Preview
PDF (licence)
SRI_deposit_agreement.pdf
Available under License : See the attached licence file.

Download (33kB) | Preview

Abstract

In this paper, we propose two methods for polyphonic Acoustic Event Detection (AED) in real life environments. The first method is based on Coupled Sparse Non-negative Matrix Factorization (CSNMF) of spectral representations and their corresponding class activity annotations. The second method is based on Multi-class Random Forest (MRF) classification of time-frequency patches. We compare the performance of the two methods on a recently published dataset TUT Sound Events 2016 containing data from home and residential area environments. Both methods show comparable performance to the baseline system proposed for DCASE 2016 Challenge on the development dataset with MRF outperforming the baseline on the evaluation dataset.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
NameEmailORCID
Sobieraj, Iwonai.sobieraj@surrey.ac.ukUNSPECIFIED
Plumbley, Markm.plumbley@surrey.ac.ukUNSPECIFIED
Date : 26 August 2016
Copyright Disclaimer : This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 03 Oct 2016 13:20
Last Modified : 11 Jul 2017 07:48
URI: http://epubs.surrey.ac.uk/id/eprint/812325

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800