In this study, we will interest in phonemes classification of Timit database using Fuzzy Logic. The fuzzy method consists in the extraction of a three fuzzy-reference vectors: maximal, mean and minimal. To classify a phoneme request, we calculate its degree of membership to all defined classes. The class of a phoneme request is, then, the one which maximizes one degree of membership calculated according to reference vectors. Different techniques of speech analysis are used for evaluation. Results show that fuzzy logic can provide a significant issue when mathematical rigor is not present as to the signal processing since the retained recognition rates was 90,85%, 22,96%, 98,57% and 91,73% for respectively MFCC, LPC, PLP and RASTA PLP.
Published in | Science Journal of Circuits, Systems and Signal Processing (Volume 2, Issue 1) |
DOI | 10.11648/j.cssp.20130201.11 |
Page(s) | 1-5 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2013. Published by Science Publishing Group |
Fuzzy Logic; MFCC; LPC; PLP; RASTA-PLP; Speech; Timit
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APA Style
Ines Ben Fredj, Kaïs Ouni. (2013). A Novel Phonemes Classification Method Using Fuzzy Logic. Science Journal of Circuits, Systems and Signal Processing, 2(1), 1-5. https://doi.org/10.11648/j.cssp.20130201.11
ACS Style
Ines Ben Fredj; Kaïs Ouni. A Novel Phonemes Classification Method Using Fuzzy Logic. Sci. J. Circuits Syst. Signal Process. 2013, 2(1), 1-5. doi: 10.11648/j.cssp.20130201.11
AMA Style
Ines Ben Fredj, Kaïs Ouni. A Novel Phonemes Classification Method Using Fuzzy Logic. Sci J Circuits Syst Signal Process. 2013;2(1):1-5. doi: 10.11648/j.cssp.20130201.11
@article{10.11648/j.cssp.20130201.11, author = {Ines Ben Fredj and Kaïs Ouni}, title = {A Novel Phonemes Classification Method Using Fuzzy Logic}, journal = {Science Journal of Circuits, Systems and Signal Processing}, volume = {2}, number = {1}, pages = {1-5}, doi = {10.11648/j.cssp.20130201.11}, url = {https://doi.org/10.11648/j.cssp.20130201.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20130201.11}, abstract = {In this study, we will interest in phonemes classification of Timit database using Fuzzy Logic. The fuzzy method consists in the extraction of a three fuzzy-reference vectors: maximal, mean and minimal. To classify a phoneme request, we calculate its degree of membership to all defined classes. The class of a phoneme request is, then, the one which maximizes one degree of membership calculated according to reference vectors. Different techniques of speech analysis are used for evaluation. Results show that fuzzy logic can provide a significant issue when mathematical rigor is not present as to the signal processing since the retained recognition rates was 90,85%, 22,96%, 98,57% and 91,73% for respectively MFCC, LPC, PLP and RASTA PLP.}, year = {2013} }
TY - JOUR T1 - A Novel Phonemes Classification Method Using Fuzzy Logic AU - Ines Ben Fredj AU - Kaïs Ouni Y1 - 2013/02/20 PY - 2013 N1 - https://doi.org/10.11648/j.cssp.20130201.11 DO - 10.11648/j.cssp.20130201.11 T2 - Science Journal of Circuits, Systems and Signal Processing JF - Science Journal of Circuits, Systems and Signal Processing JO - Science Journal of Circuits, Systems and Signal Processing SP - 1 EP - 5 PB - Science Publishing Group SN - 2326-9073 UR - https://doi.org/10.11648/j.cssp.20130201.11 AB - In this study, we will interest in phonemes classification of Timit database using Fuzzy Logic. The fuzzy method consists in the extraction of a three fuzzy-reference vectors: maximal, mean and minimal. To classify a phoneme request, we calculate its degree of membership to all defined classes. The class of a phoneme request is, then, the one which maximizes one degree of membership calculated according to reference vectors. Different techniques of speech analysis are used for evaluation. Results show that fuzzy logic can provide a significant issue when mathematical rigor is not present as to the signal processing since the retained recognition rates was 90,85%, 22,96%, 98,57% and 91,73% for respectively MFCC, LPC, PLP and RASTA PLP. VL - 2 IS - 1 ER -