A parallel distributed processing model of visual word recognition and pronunciation is described. The model consists of sets of orthographic and phonological units and an interlevel of hidden units. Weights on connections between units were modified during a training phase using the back

Abstract-This paper reports on an optimum dynamic programming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using timewarping function. Then, two time-normalized distance definitions, ded symmetric and asymmetric forms

Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary in-cluded many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain

spoken word recognition 1

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with Japanese students and activities for engaging students in active reading are also discussed. Problems Japanese students experience with reading English include giving equal weight to each word, failure to understand the connections among sentences in a paragraph and difficulty in summarizing passages

process. At the end of grade 2, students in the basal reader treatment showed significantly superior achievement in word study skills, spelling, and oral reading accuracy. At the end of grade 3, students in the linguistic group showed superiorperformance in the rate of oral reading and number of words

A word recognition architecture based on a network of neural associative memories and hidden Markov models has been developed. The input stream, composed of subword-units like wordinternal triphones consisting of diphones and triphones, is provided to the network of neural associative memories

We describe a Hidden Markov Model (HMM) based word recognition engine currently being developed to be integrated with the CENPARMI Bank Cheque Processing System. The various modules are described in detail, and preliminary results are compared with our previous global feature recognition scheme

in word recognition are reviewed and then assessed through four experiments. The purpose of the first experiment was to examine some basic aspects of the processing of words, pseudowords, and nonwords, and beyond that, to discover basic differences in their processing that might underlie the word