Third International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA 2003)

Florence, Italy
December 10-12, 2003

Algorithm of Phoneme Identification Using Fast Measurement of Wiener Kernels of Speech Signals

A. M. Krot (1), P. P. Tkachova (2)

(1) United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Belarus
(2) Belarusian State University, Minsk, Belarus

The nonlinear speech signal decomposition based on Volterra-Wiener functional series is described. The solution of speech recognition problem by means of measuring Wiener kernels is proposed. The recognition system of speech signal is considered for speech phoneme identification.

Index Terms. Nonlinear signal decomposition, Wiener kernels, phoneme recognition

Full Paper (reprinted with permission from Firenze University Press)

Bibliographic reference.  Krot, A. M. / Tkachova, P. P. (2003): "Algorithm of phoneme identification using fast measurement of Wiener kernels of speech signals", In MAVEBA-2003, 107-110.