Publications

Abstract

The Possible Word Constraint is a proposed mechanism whereby listeners avoid recognising words spuriously embedded in other words. It applies to words leaving a vowelless residue between their edge and the nearest known word or syllable boundary. The present study tests the usefulness of this constraint via lexical statistics of both English and Dutch. The analyses demonstrate that the constraint removes a clear majority of embedded words in speech, and thus can contribute significantly to the efficiency of human speech recognition

Abstract

Recognizing spoken language involves automatic activation of multiple candidate words. The process of selection between candidates is made more efficient by inhibition of embedded words (like egg in beg) that leave a portion of the input stranded (here, b). Results from European languages suggest that this inhibition occurs when consonants are stranded but not when syllables are stranded. The reason why leftover syllables do not lead to inhibition could be that in principle they might themselves be words; in European languages, a syllable can be a word. In Sesotho (a Bantu language), however, a single syllable cannot be a word. We report that in Sesotho, word recognition is inhibited by stranded consonants, but stranded monosyllables produce no more difficulty than stranded bisyllables (which could be Sesotho words). This finding suggests that the viability constraint which inhibits spurious embedded word candidates is not sensitive to language-specific word structure, but is universal.

Abstract

In four experiments, we examined the facilitation that occurs when spoken-word targets rhyme with preceding spoken primes. In Experiment 1, listeners’ lexical decisions were faster to words following rhyming words (e.g., ramp–LAMP) than to words following unrelated primes (e.g., pink–LAMP). No facilitation was observed for nonword targets. Targets that almost rhymed with their primes (foils; e.g., bulk–SULSH) were included in Experiment 2; facilitation for rhyming targets was severely attenuated. Experiments 3 and 4 were single-word shadowing variants of the earlier experiments. There was facilitation for both rhyming words and nonwords; the presence of foils had no significant influence on the priming effect. A major component of the facilitation in lexical decision appears to be strategic: Listeners are biased to say “yes” to targets that rhyme with their primes, unless foils discourage this strategy. The nonstrategic component of phonological facilitation may reflect speech perception processes that operate prior to lexical access.

Abstract

Spoken word recognition involves automatic activation of lexical candidates compatible with the perceived input. In running speech, words abut one another without intervening gaps, and syllable boundaries can mismatch with word boundaries. For instance, liaison in ’petit agneau’ creates a syllable beginning with a consonant although ’agneau’ begins with a vowel. In two cross-modal priming experiments we investigate how French listeners recognise words in liaison environments. These results suggest that the resolution of liaison in part depends on acoustic cues which distinguish liaison from non-liaison consonants, and in part on the availability of lexical support for a liaison interpretation.

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

In a 50,000-word corpus of spoken British English the occurrence of words embedded within other words is reported. Within-word embedding in this real speech sample is common, and analogous to the extent of embedding observed in the vocabulary. Imposition of a syllable boundary matching constraint reduces but by no means eliminates spurious embedding. Embedded words are most likely to overlap with the beginning of matrix words, and thus may pose serious problems for speech recognisers.

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

This paper describes recent experimental evidence which shows that models of spoken word recognition must incorporate both inhibition between competing lexical candidates and a sensitivity to metrical cues to lexical segmentation. A new version of the Shortlist [1][2] model incorporating the Metrical Segmentation Strategy [3] provides a detailed simulation of the data.