Abstract
This paper describes an algorithm for the automatic parsing of continuous speech into a string of syllables, intended for use as the “front end” of a demisyllable‐based continuous speech recognizer. The algorithm takes an input an autocorrelation coefficient (ACC) parameterization of speech, an analysis independently required for our recognition process; it makes use of only the zeroth‐order ACC (energy) and normalized first‐order ACC. Local maxima in a severely low‐pass‐filtered representation of the energy signal determine potential syllabic nuclei. Some of these first‐pass syllables are discarded on the basis of further tests. Compared to other syllable parsers described in the literature, this algorithm (1) was designed and tested for use with telephone speech, i.e., utterances spoken into a carbon microphone over a dialed‐up phone line and bandpass filtered to 200–3200 Hz; (2) locates potential syllabic nuclei by reference to the simple energy signal, rather than to a spectrally weighted “loudness” t...
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