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Automatic text clustering for audio attribute elicitation experiment responses

Francombe, Jon, Brookes, Timothy and Mason, Russell (2017) Automatic text clustering for audio attribute elicitation experiment responses In: AES 143rd Convention, 18 - 21 October 2017, New York, USA.

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Abstract

Collection of text data is an integral part of descriptive analysis, a method commonly used in audio quality evaluation experiments. Where large text data sets will be presented to a panel of human assessors (e.g., to group responses that have the same meaning), it is desirable to reduce redundancy as much as possible in advance. Text clustering algorithms have been used to achieve such a reduction. A text clustering algorithm was tested on a dataset for which manual annotation by two experts was also collected. The comparison between the manual annotations and automatically-generated clusters enabled evaluation of the algorithm. While the algorithm could not match human performance, it could produce a similar grouping with a significant redundancy reduction (approximately 48%).

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Arts and Social Sciences > School of Arts > Music
Authors :
NameEmailORCID
Francombe, Jonj.francombe@surrey.ac.ukUNSPECIFIED
Brookes, TimothyT.Brookes@surrey.ac.ukUNSPECIFIED
Mason, RussellR.Mason@surrey.ac.ukUNSPECIFIED
Date : 8 October 2017
Funders : Engineering and Physical Sciences Research Council (EPSRC)
Grant Title : Grant S3A: Future Spatial Audio for an Immersive Listener Experience at Home
Copyright Disclaimer : Copyright 2017 Audio Engineering Society. This paper will be available in the AES E-Library (http://www.aes.org/e-lib), all rights reserved. Reproduction of this paper, or any portion thereof, is not permitted without direct permission from the Journal of the Audio Engineering Society.
Additional Information : Paper Number: 9843. Details about the data underlying this work, along with the terms for data access, are available from http://dx.doi.org/10.15126/surreydata.00841589
Depositing User : Melanie Hughes
Date Deposited : 18 Aug 2017 08:23
Last Modified : 31 Oct 2017 15:11
URI: http://epubs.surrey.ac.uk/id/eprint/841962

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