ZCPA Features for Speech Recognition Implementation into MASPER training procedure for Slovak language

In this article we present implementation, modifications and optimization of zero-crossing peak amplitude (ZCPA) speech feature extraction method into Slovak speech recognition system. ZCPA features are closely mimicking the human auditory system in the time domain, and thus they should be more robust against common noises. Except the basic configuration several modifications have been suggested, implemented and evaluated. Furthermore, optimization of settings on a real system using professional database and MASPER training procedure have been found and compared to classical features presented by MFCC and PLP in different scenarios and noise conditions.