Publications

Abstract

The recognition of speech involves the segmentation of continuous utterances into their component words. Cross-linguistic evidence is briefly reviewed which suggests that although there are language-specific solutions to this segmentation problem, they have one thing in common: they are all based on language rhythm. In English, segmentation is stress-based: strong syllables are postulated to be the onsets of words. Segmentation, however, can also be achieved by a process of competition between activated lexical hypotheses, as in the Shortlist model. A series of experiments is summarised showing that segmentation of continuous speech depends on both lexical competition and a metrically-guided procedure. In the final section, the implementation of metrical segmentation in the Shortlist model is described: the activation of lexical hypotheses matching strong syllables in the input is boosted and that of hypotheses mismatching strong syllables in the input is penalised.

Abstract

Japanese listeners detect speech sound targets which correspond precisely to a mora (a phonological unit which is the unit of rhythm in Japanese) more easily than targets which do not. English listeners detect medial vowel targets more slowly than consonants. Six phoneme detection experiments investigated these effects in both subject populations, presented with native- and foreign-language input. Japanese listeners produced faster and more accurate responses to moraic than to nonmoraic targets both in Japanese and, where possible, in English; English listeners responded differently. The detection disadvantage for medial vowels appeared with English listeners both in English and in Japanese; again, Japanese listeners responded differently. Some processing operations which listeners apply to speech input are language-specific; these language-specific procedures, appropriate for listening to input in the native language, may be applied to foreign-language input irrespective of whether they remain appropriate.

Abstract

Although word boundaries are rarely clearly marked, listeners can rapidly recognize the individual words of spoken sentences. Some theories explain this in terms of competition between multiply activated lexical hypotheses; others invoke sensitivity to prosodic structure. We describe a connectionist model, SHORTLIST, in which recognition by activation and competition is successful with a realistically sized lexicon. Three experiments are then reported in which listeners detected real words embedded in nonsense strings, some of which were themselves the onsets of longer words. Effects both of competition between words and of prosodic structure were observed, suggesting that activation and competition alone are not sufficient to explain word recognition in continuous speech. However, the results can be accounted for by a version of SHORTLIST that is sensitive to prosodic structure.

Abstract

Word-initial CVC syllables are detected faster in words beginning consonant-vowel-consonant-vowel (CVCV-) than in words beginning consonant-vowel-consonant-consonant (CVCC-). This effect was reported independently by M. Taft and G. Hambly (1985, Journal of Memory and Language, 24, 320–335) and by A. Cutler, J. Mehler, D. Norris, and J. Segui (1986, Journal of Memory and Language, 25, 385–400). Taft and Hambly explained the effect in terms of lexical factors. This explanation cannot account for Cutler et al.'s results, in which the effect also appeared with nonwords and foreign words. Cutler et al. suggested that CVCV-sequences might simply be easier to perceive than CVCC-sequences. The present study confirms this suggestion, and explains it as a reflection of listener expectations constructed on the basis of distributional characteristics of the language.

Abstract

Studies of human speech processing have provided evidence for a segmentation strategy in the perception of continuous speech, whereby a word boundary is postulated, and a lexical access procedure initiated, at each metrically strong syllable. The likely success of this strategy was here estimated against the characteristics of the English vocabulary. Two computerized dictionaries were found to list approximately three times as many words beginning with strong syllables (i.e. syllables containing a full vowel) as beginning with weak syllables (i.e. syllables containing a reduced vowel). Consideration of frequency of lexical word occurrence reveals that words beginning with strong syllables occur on average more often than words beginning with weak syllables. Together, these findings motivate an estimate for everyday speech recognition that approximately 85% of lexical words (i.e. excluding function words) will begin with strong syllables. This estimate was tested against a corpus of 190 000 words of spontaneous British English conversion. In this corpus, 90% of lexical words were found to begin with strong syllables. This suggests that a strategy of postulating word boundaries at the onset of strong syllables would have a high success rate in that few actual lexical word onsets would be missed.