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dc.contributor.authorKong, Ying-Yee
dc.contributor.authorMullangi, Ala
dc.contributor.authorKokkinakis, Kostas
dc.date.accessioned2014-05-01T18:02:14Z
dc.date.available2014-05-01T18:02:14Z
dc.date.issued2014-04-18
dc.identifier.citationKong Y-Y, Mullangi A, Kokkinakis K (2014) Classification of Fricative Consonants for Speech Enhancement in Hearing Devices. PLoS ONE 9(4): e95001. http://dx.doi.org/10.1371/journal.pone.0095001
dc.identifier.urihttp://hdl.handle.net/1808/13614
dc.description.abstractObjective To investigate a set of acoustic features and classification methods for the classification of three groups of fricative consonants differing in place of articulation. Method A support vector machine (SVM) algorithm was used to classify the fricatives extracted from the TIMIT database in quiet and also in speech babble noise at various signal-to-noise ratios (SNRs). Spectral features including four spectral moments, peak, slope, Mel-frequency cepstral coefficients (MFCC), Gammatone filters outputs, and magnitudes of fast Fourier Transform (FFT) spectrum were used for the classification. The analysis frame was restricted to only 8 msec. In addition, commonly-used linear and nonlinear principal component analysis dimensionality reduction techniques that project a high-dimensional feature vector onto a lower dimensional space were examined. Results With 13 MFCC coefficients, 14 or 24 Gammatone filter outputs, classification performance was greater than or equal to 85% in quiet and at +10 dB SNR. Using 14 Gammatone filter outputs above 1 kHz, classification accuracy remained high (greater than 80%) for a wide range of SNRs from +20 to +5 dB SNR. Conclusions High levels of classification accuracy for fricative consonants in quiet and in noise could be achieved using only spectral features extracted from a short time window. Results of this work have a direct impact on the development of speech enhancement algorithms for hearing devices.
dc.description.sponsorshipThis work was supported by NIH/NIDCD R01-DC-012300 to Y-YK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
dc.publisherPublic Library of Science
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleClassification of Fricative Consonants for Speech Enhancement in Hearing Devices
dc.typeArticle
kusw.kuauthorKokkinakis, Kostas
kusw.kudepartmentSpeech-Language-Hearing
kusw.oastatusfullparticipation
dc.identifier.doi10.1371/journal.pone.0095001
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Except where otherwise noted, this item's license is described as: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.