TY  - JOUR
AU  - Lileikyte, R.
AU  - Telksnys, L.
PY  - 2011/06/08
Y2  - 2025/01/02
TI  - Quality Estimation Methodology of Speech Recognition Features
JF  - Elektronika ir Elektrotechnika
JA  - ELEKTRON ELEKTROTECH
VL  - 110
IS  - 4
SE  - 
DO  - 10.5755/j01.eee.110.4.302
UR  - https://eejournal.ktu.lt/index.php/elt/article/view/302
SP  - 113-116
AB  - The best feature set selection is the key of successful speech recognition system. Quality measure is needed to characterize the chosen feature set. Variety of feature quality metrics are proposed by other authors. However, no guidance is given to choose the appropriate metric. Also no metrics investigations for speech features were made. In the paper the methodology for quality estimation of speech features is presented. Metrics have to be chosen on the ground of their correlation with classification results. Linear Frequency Cepstrum (LFCC), Mel Frequency Cepstrum (MFCC), Perceptual Linear Prediction (PLP) analyses were selected for experiment. The most proper metric was chosen in combination with Dynamic Time Warping (DTW) classifier. Experimental investigation results are presented. Ill. 5, bibl. 18, tabl. 3 (in English; abstracts in English and Lithuanian).<p><a href="http://dx.doi.org/10.5755/j01.eee.110.4.302">http://dx.doi.org/10.5755/j01.eee.110.4.302</a></p>
ER  -