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Application of sequential decoding for converting phonetic to graphic representation in automatic recognition of continuous speech(ARCS)

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3 Author(s)
Tappert, C. ; IBM Thomas J. Watson Research Center, Yorktown Heights, New York ; Dixon, N. ; Rabinowitz, A.

Following segmentation and phonetic classification in automatic recognition of continuous speech (ARCS), it is necessary to provide methods for linguistic decoding, In this work a graph search procedure, based on the Fano algorithm, is used to convert machine-contaminated phonetic descriptions of speaker performance into standard orthography. The information utilized by the decoder consists of a syntax, a lexicon containing transcription variation for each word, and performance-based statistics from acoustic analysis. The latter contain information related to automatic segmentation and classification accuracy and certainty (anchor-point) data. A distinction is made between speaker- and machine-dependent corruption of phonetic input strings. Preliminary results are presented and discussed, together with some considerations for evaluation.

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Audio and Electroacoustics, IEEE Transactions on  (Volume:21 ,  Issue: 3 )