Abstract

Systems designed to recognize continuous speech must be able to adapt to many types of acoustic variation, including variations in stress. A speaker-dependent recognition study was conducted on a group of stressed and destressed syllables. These syllables, some containing the short vowel /I/ and others the long vowel /ae/, were excised from continuous speech and transformed into arrays of cepstral coefficients at two levels of precision. From these data, four types of template dictionaries varying in size and stress composition were formed by a time-warping procedure. Recognition performance data were gathered from listeners and from a computer recognition algorithm that also employed warping. It was found that for a significant portion of the data base, stressed and destressed versions of the same syllable are sufficiently different from one another as to justify the use of separate dictionary templates. Second, destressed syllables exhibit roughly the same acoustic variance as their stressed counterparts. Third, long vowels tend to be involved in proportionally fewer cross-vowel errors but tend to diminish the warping algorithm's ability to discriminate consonantal information. Finally, the pattern of consonant errors that listeners make as a function of vowel length shows significant differences from that produced by the computer.

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