Direct electrical stimulation of the auditory nerve can be used to restore some degree of hearing to the profoundly deaf. Percepts due to electrical stimulation have characteristics corresponding approximately to the acoustic percepts of loudness, pitch, and timbre. To encode speech as a pattern of electrical stimulation, it is necessary to determine the effects of the stimulus parameters on these percepts. The effects of the three basic stimulus parameters of level, repetition rate, and stimulation location on subjects' percepts were examined. Pitch difference limens arising from changes in rate of stimulation increase as the stimulating rate increases, up to a saturation point of between 200 and 1000 pulses per second. Changes in pitch due to electrode selection depend upon the subject, but generally agree with a tonotopic organization of the human cochlea. Further, the discriminability of such place-pitch percepts seems to be dependent on the degree of current spread in the cochlea. The effect of stimulus level on perceived pitch is significant but is highly dependent on the individual tested. The results of these experiments are discussed in terms of their impact on speech-processing strategies and their relevance to acoustic pitch perception.

Despite their known weaknesses, hidden Markov models (HMMs) have been the dominant technique for acoustic modeling in speech recognition for over two decades. Still, the advances in the HMM framework have not solved its key problems: it discards information about time dependencies and is prone to overgeneralization. In this paper, we attempt to overcome these problems by relying on straightforward template matching. The basis for the recognizer is the well-known DTW algorithm. However, classical DTW continuous speech recognition results in an explosion of the search space. The traditional top-down search is therefore complemented with a data-driven selection of candidates for DTW alignment. We also extend the DTW framework with a flexible subword unit mechanism and a class sensitive distance measure-two components suggested by state-of-the-art HMM systems. The added flexibility of the unit selection in the template-based framework leads to new approaches to speaker and environment adaptation. The template matching system reaches a performance somewhat worse than the best published HMM results for the Resource Management benchmark, but thanks to complementarity of errors between the HMM and DTW systems, the combination of both leads to a decrease in word error rate with 17% compared to the HMM results.

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