Comparison of Different Spectral Parameters in the Problem of Automatic Recognition of American English Vowels

Student: Grammatchikova Elena

Supervisor: Anastasiya A. Bonch-Osmolovskaya

Educational Programme: Language Theory and Computational Linguistics (Master)

Final Grade: 10

Year of Graduation: 2017

Current work is devoted to investigation of effectiveness of the four parametric representations of the acoustic signal (Mel Frequency Cepstral Coefficients – MFCC; Line Spectral Pairs – LSF; Linear Predictive Cepstral Coefficients – LPCC; Cepstral Distance based LPCC – CD-LPCC) concerning the problem of automatic recognition of American English vowels based on the minimum-volume ellipsoids classifier. The results obtained for each set of parameters allow to draw a conclusion that MFCCs are the most informative parametric representation of the acoustic signal in the problem of automatic vowel classification.

Full text (added June 1, 2017)

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