We present a framework to apply Volterra series to analyze multilayered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. Th...
Joel Pinto, Garimella S. V. S. Sivaram, Hynek Herm...
Speech recognition technology suffers from a lack of robustness which limits its usability for fully automated speech-to-text transcription, and manual correction is generally req...
Noise power spectral density estimation is an important component of speech enhancement systems due to its considerable effect on the quality and the intelligibility of the enhanc...
Human brain is exceptionally complex and simple at the same time. Its extremely composite biological structure results itself in human everyday behavior that many people might cons...
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...