title: A two-step segmentation method for automatic recognition of speech of persons who are deaf.
abstract: The development and use of a two-step word segmentation method for automatic recognition of the speech produced by deaf persons are described in this paper. This method incorporates the segmental and temporal characteristics of deaf speech, particularly the intra- and inter-word pauses, to achieve accurate recognition. In the first step, estimates of word boundaries were obtained by detecting these pauses. In the second step, the word boundaries were determined by matching all possible groupings of speech segments against all reference templates during recognition. This method was applied to recognition of isolated words and connected-speech utterances produced by two deaf speakers. Recognition rates of 93.01 percent and 81.81 percent were obtained in recognizing isolated words and connected speech, respectively.
authors.affiliation: Department of Biomedical Engineering, Louisiana Tech University, Ruston 71272.
authors.forename: K A
authors.initials: KA
authors.lastname: Abdelhamied
authors.forename: M B
authors.initials: MB
authors.lastname: Waldron
authors.forename: R A
authors.initials: RA
authors.lastname: Fox
mesh_terms: D000465:Algorithms; D003638:Deafness / Q000534:rehabilitation*; D006801:Humans; D008297:Male; D013065:Speech Intelligibility; D013067:Speech Perception; D013068:Speech Production Measurement