The goal of this paper is the application of the Genetic Algorithms (GAs) to the Automatic Speech Recognition (ASR) domain at the acoustic sequences classification level. Thus, we have looked for recognizing Standard Arabic (SA) stop sounds of continuous, naturally spoken, speech. We have used GAs because of their advantages in resolving complicated optimization problems, where analytic methods...

Previous studies of the neural representation of speech assumed some form of neural code, usually discharge rate or phase locking, for the representation. In the present study, responses to five synthesized CVC_CV (e.g., /dad_da/) utterances have been examined using information-theoretic distance measures [or Kullback-Leibler (KL) distance] that are independent of a priori assumptions about the...

When spectral properties differ across successive sounds, this difference is perceptually magnified, resulting in spectral contrast effects (SCEs). Recently, Stilp, Anderson, and Winn [(2015) J. Acoust. Soc. Am. 137(6), 3466-3476] revealed that SCEs are graded: more prominent spectral peaks in preceding sounds produced larger SCEs (i.e., category boundary shifts) in categorization of subsequent...

Speech signals from stop consonants with trailing vowels were analysed for cues consistent with their place of articulation. They were decomposed into periodic and aperiodic components by the pitch-scaled harmonic filter to improve the quality of the formant tracks, to which exponential trajectories were fitted to get robust formant loci at voice onset. Ensemble-average power spectra of the bur...