Harsha Sathyendra

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The standards that are still in use for telephone communications since the 1950s limit the information bandwidth to 300-3400Hz. However, in normal conversational speech, the frequency content is mainly between 0-8000Hz. This constraint degrades not only the sound quality but also the intelligibility of the transmitted signal. Instead of modifying the(More)
We propose a noise robust feature extraction technique for speech signals using phase synchrony. The front-end employs a psychoacoustic cochlea model with inner hair cells to transform speech into a parallel stream of spike trains as observed in the auditory nerve fibers. The degree of phase synchrony among nerve fibers with similar characteristic(More)
Shortcomings of automatic speech recognition (ASR) applications are becoming more evident as they are more widely used in real life. The inherent non-stationarity associated with the timing of speech signals as well as the dynamical changes in the environment make the ensuing analysis and recognition extremely difficult. Researchers often turn to biology(More)
We propose a duplex theory of spike coding in the early stages of the auditory system based on the intensity and noise levels of the acoustic stimuli. According to this concept, at low intensity levels, where auditory nerve firings cannot generate a high enough synchrony among neuron ensembles, rate coding is more likely favored against phase-locking via(More)
of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy A BIOLOGICALLY PLAUSIBLE APPROACH FOR NOISE ROBUST VOWEL RECOGNITION By Ismail Uysal August 2008 Chair: John G. Harris Major: Electrical and Computer Engineering Present day commercial automatic(More)
The field of automatic speech recognition (ASR) has advanced far enough in the past decade to produce numerous commercial applications such as the speech-driven telephone customer service menus now deployed by many companies. Unfortunately, these and other state-of-the-art ASR systems still pale in comparison to human performance, particularly in the(More)
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