Quality Estimation Methodology of Speech Recognition Features
DOI:
https://doi.org/10.5755/j01.eee.110.4.302Abstract
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).Downloads
Published
2011-06-08
How to Cite
Lileikyte, R., & Telksnys, L. (2011). Quality Estimation Methodology of Speech Recognition Features. Elektronika Ir Elektrotechnika, 110(4), 113-116. https://doi.org/10.5755/j01.eee.110.4.302
Issue
Section
SIGNAL TECHNOLOGY
License
The copyright for the paper in this journal is retained by the author(s) with the first publication right granted to the journal. The authors agree to the Creative Commons Attribution 4.0 (CC BY 4.0) agreement under which the paper in the Journal is licensed.
By virtue of their appearance in this open access journal, papers are free to use with proper attribution in educational and other non-commercial settings with an acknowledgement of the initial publication in the journal.
