TY  - JOUR
AU  - Topalović, Marko
AU  - Damnjanović, Đorđe
AU  - Peulić, Aleksandar
AU  - Blagojević, Milan
AU  - Filipović, Nenad
PY  - 2015
UR  - https://gery.gef.bg.ac.rs/handle/123456789/708
AB  - During the speech, contractions of muscles in the speech apparatus produce myoelectric signals that can be picked up by electrodes, filtered and analyzed. The problem of extraction of speech information from these signals is significant for patients with damaged speech apparatus, such as laryngectomy patients, who could use speech recognition based on myoelectric signal classification to communicate by means of the synthetic speech. In the most previously conducted research, classification is performed on a ten word vocabulary which resulted in a good classification rate. In this paper, a possibility for myoelectric syllable based speech classification is analyzed on a significantly larger vocabulary with novel decision set based classifier which is simple, easy to adapt, convenient for research and similar to the way humans think. In order to have a high quality of recorded myoelectric signals, analysis of the optimal position of electrodes is performed. classification is performed by comparison between syllable combination and whole words. Based on classification rate, words can belong to easy, medium or hard to distinguish group. Results based on generated list of best matching combinations show that decision set analysis of myoelectric signals for speech recognition is a promising novel method.
PB  - World Scientific Publ Co Pte Ltd, Singapore
T2  - Biomedical Engineering-Applications Basis Communications
T1  - Syllable-based speech recognition using electromyography and decision set classifier
VL  - 27
IS  - 2
DO  - 10.4015/S1016237215500209
UR  - https://hdl.handle.net/21.15107/rcub_gery_708
ER  - 

@article{
author = "Topalović, Marko and Damnjanović, Đorđe and Peulić, Aleksandar and Blagojević, Milan and Filipović, Nenad",
year = "2015",
abstract = "During the speech, contractions of muscles in the speech apparatus produce myoelectric signals that can be picked up by electrodes, filtered and analyzed. The problem of extraction of speech information from these signals is significant for patients with damaged speech apparatus, such as laryngectomy patients, who could use speech recognition based on myoelectric signal classification to communicate by means of the synthetic speech. In the most previously conducted research, classification is performed on a ten word vocabulary which resulted in a good classification rate. In this paper, a possibility for myoelectric syllable based speech classification is analyzed on a significantly larger vocabulary with novel decision set based classifier which is simple, easy to adapt, convenient for research and similar to the way humans think. In order to have a high quality of recorded myoelectric signals, analysis of the optimal position of electrodes is performed. classification is performed by comparison between syllable combination and whole words. Based on classification rate, words can belong to easy, medium or hard to distinguish group. Results based on generated list of best matching combinations show that decision set analysis of myoelectric signals for speech recognition is a promising novel method.",
publisher = "World Scientific Publ Co Pte Ltd, Singapore",
journal = "Biomedical Engineering-Applications Basis Communications",
title = "Syllable-based speech recognition using electromyography and decision set classifier",
volume = "27",
number = "2",
doi = "10.4015/S1016237215500209",
url = "https://hdl.handle.net/21.15107/rcub_gery_708"
}

Topalović, M., Damnjanović, Đ., Peulić, A., Blagojević, M.,& Filipović, N.. (2015). Syllable-based speech recognition using electromyography and decision set classifier. in Biomedical Engineering-Applications Basis Communications
World Scientific Publ Co Pte Ltd, Singapore., 27(2).
https://doi.org/10.4015/S1016237215500209
https://hdl.handle.net/21.15107/rcub_gery_708

Topalović M, Damnjanović Đ, Peulić A, Blagojević M, Filipović N. Syllable-based speech recognition using electromyography and decision set classifier. in Biomedical Engineering-Applications Basis Communications. 2015;27(2).
doi:10.4015/S1016237215500209
https://hdl.handle.net/21.15107/rcub_gery_708 .

Topalović, Marko, Damnjanović, Đorđe, Peulić, Aleksandar, Blagojević, Milan, Filipović, Nenad, "Syllable-based speech recognition using electromyography and decision set classifier" in Biomedical Engineering-Applications Basis Communications, 27, no. 2 (2015),
https://doi.org/10.4015/S1016237215500209 .,
https://hdl.handle.net/21.15107/rcub_gery_708 .