Classification of Fricative Consonants for Speech Enhancement in Hearing Devices
dc.contributor.author | Kong, Ying-Yee | |
dc.contributor.author | Mullangi, Ala | |
dc.contributor.author | Kokkinakis, Kostas | |
dc.date.accessioned | 2014-05-01T18:02:14Z | |
dc.date.available | 2014-05-01T18:02:14Z | |
dc.date.issued | 2014-04-18 | |
dc.identifier.citation | Kong 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.uri | http://hdl.handle.net/1808/13614 | |
dc.description.abstract | Objective 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.sponsorship | This 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.publisher | Public Library of Science | |
dc.rights | 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. | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.title | Classification of Fricative Consonants for Speech Enhancement in Hearing Devices | |
dc.type | Article | |
kusw.kuauthor | Kokkinakis, Kostas | |
kusw.kudepartment | Speech-Language-Hearing | |
kusw.oastatus | fullparticipation | |
dc.identifier.doi | 10.1371/journal.pone.0095001 | |
kusw.oaversion | Scholarly/refereed, publisher version | |
kusw.oapolicy | This item meets KU Open Access policy criteria. | |
dc.rights.accessrights | openAccess |
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