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

Several models of spoken word recognition postulate that recognition is achieved via a process of competition between lexical hypotheses. Competition not only provides a mechanism for isolated word recognition, it also assists in continuous speech recognition, since it offers a means of segmenting continuous input into individual words. We present statistics on the pattern of occurrence of words embedded in the polysyllabic words of the English vocabulary, showing that an overwhelming majority (84%) of polysyllables have shorter words embedded within them. Positional analyses show that these embeddings are most common at the onsets of the longer word. Although both phonological and syntactic constraints could rule out some embedded words, they do not remove the problem. Lexical competition provides a means of dealing with lexical embedding. It is also supported by a growing body of experimental evidence. We present results which indicate that competition operates both between word candidates that begin at the same point in the input and candidates that begin at different points (McQueen, Norris, & Cutler, 1994, Noms, McQueen, & Cutler, in press). We conclude that lexical competition is an essential component in models of continuous speech recognition.

Abstract

Spoken utterances contain few reliable cues to word boundaries, but listeners nonetheless experience little difficulty identifying words in continuous speech. The authors present data and simulations that suggest that this ability is best accounted for by a model of spoken-word recognition combining competition between alternative lexical candidates and sensitivity to prosodic structure. In a word-spotting experiment, stress pattern effects emerged most clearly when there were many competing lexical candidates for part of the input. Thus, competition between simultaneously active word candidates can modulate the size of prosodic effects, which suggests that spoken-word recognition must be sensitive both to prosodic structure and to the effects of competition. A version of the Shortlist model ( D. G. Norris, 1994b) incorporating the Metrical Segmentation Strategy ( A. Cutler & D. Norris, 1988) accurately simulates the results using a lexicon of more than 25,000 words.

Abstract

This paper presents lexical statistics on the pattern of occurrence of words embedded in other words. We report the results of an analysis of 25000 words, varying in length from two to six syllables, extracted from a phonetically-coded English dictionary (The Longman Dictionary of Contemporary English). Each syllable, and each string of syllables within each word was checked against the dictionary. Two analyses are presented: the first used a complete list of polysyllables, with look-up on the entire dictionary; the second used a sublist of content words, counting only embedded words which were themselves content words. The results have important implications for models of human speech recognition. The efficiency of these models depends, in different ways, on the number and location of words within words.