Publications

Abstract

The results of a study on perceptual learning are reported. Dutch subjects made lexical decisions on a list of words and nonwords. Embedded in the list were either [f]- or [s]-final words in which the final fricative had been replaced by an ambiguous sound, midway between [f] and [s]. One group of listeners heard ambiguous [f]- final Dutch words like [kara?] (based on karaf, carafe) and unambiguous [s]-final words (e.g., karkas, carcase). A second group heard the reverse (e.g., ambiguous [karka?] and unambiguous karaf). After this training phase, listeners labelled ambiguous fricatives on an [f]- [s] continuum. The subjects who had heard [?] in [f]- final words categorised these fricatives as [f] reliably more often than those who had heard [?] in [s]-final words. These results suggest that speech recognition is dynamic: the system adjusts to the constraints of each particular listening situation. The lexicon can provide this adjustment process with a training signal.

Abstract

We introduce the papers in this special issue by summarising the current major issues in spoken word recognition. We argue that a full understanding of the process of lexical access during speech comprehension will depend on resolving several key representational issues: what is the form of the representations used for lexical access; how is phonological information coded in the mental lexicon; and how is the morphological and semantic information about each word stored? We then discuss a number of distinct access processes: competition between lexical hypotheses; the computation of goodness-of-fit between the signal and stored lexical knowledge; segmentation of continuous speech; whether the lexicon influences prelexical processing through feedback; and the relationship of form-based processing to the processes responsible for deriving an interpretation of a complete utterance. We conclude that further progress may well be made by swapping ideas among the different sub-domains of the discipline.

Abstract

In two word-spotting experiments, Japanese listeners detected Japanese words faster in vowel contexts (e.g., agura, to sit cross-legged, in oagura) than in consonant contexts (e.g., tagura). In the same experiments, however, listeners spotted words in vowel contexts (e.g., saru, monkey, in sarua) no faster than in moraic nasal contexts (e.g., saruN). In a third word-spotting experiment, words like uni, sea urchin, followed contexts consisting of a consonant-consonant-vowel mora (e.g., gya) plus either a moraic nasal (gyaNuni), a vowel (gyaouni) or a consonant (gyabuni). Listeners spotted words as easily in the first as in the second context (where in each case the target words were aligned with mora boundaries), but found it almost impossible to spot words in the third (where there was a single consonant, such as the [b] in gyabuni, between the beginning of the word and the nearest preceding mora boundary). Three control experiments confirmed that these effects reflected the relative ease of segmentation of the words from their contexts.We argue that the listeners showed sensitivity to the viability of sound sequences as possible Japanese words in the way that they parsed the speech into words. Since single consonants are not possible Japanese words, the listeners avoided lexical parses including single consonants and thus had difficulty recognizing words in the consonant contexts. Even though moraic nasals are also impossible words, they were not difficult segmentation contexts because, as with the vowel contexts, the mora boundaries between the contexts and the target words signaled likely word boundaries. Moraic rhythm appears to provide Japanese listeners with important segmentation cues.

Abstract

Two word-spotting experiments are reported that examine whether the Possible-Word Constraint (PWC) is a language-specific or language-universal strategy for the segmentation of continuous speech. The PWC disfavours parses which leave an impossible residue between the end of a candidate word and any likely location of a word boundary, as cued in the speech signal. The experiments examined cases where the residue was either a CVC syllable with a schwa, or a CV syllable with a lax vowel. Although neither of these syllable contexts is a possible lexical word in English, word-spotting in both contexts was easier than in a context consisting of a single consonant. Two control lexical-decision experiments showed that the word-spotting results reflected the relative segmentation difficulty of the words in different contexts. The PWC appears to be language-universal rather than language-specific.

Abstract

Sentential context effects on the identification of the Dutch function words te (to) and de (the) were examined. In Experiment 1, listeners labeled words on a [tә]-[dә] continuum more often as te when the context was te biased (Ik probeer [?ә] schieten [I try to/the shoot]) than when it was de biased (Ik probeer [?ә] schoenen [I try to/the shoes]). The effect was weaker in slower responses. In Experiment 2, disambiguation began later, in the second word after [?ә]. There was a weak context effect only in the slower responses. In Experiments 3 and 4, disambiguation occurred on the word before [?ә]: There was no context effect when one set of sentences was used, but there was an effect (larger in the faster responses) when more sentences were used. Syntactic processing affects word identification only within a limited time frame. It appears to do so not by influencing lexical access processes through feedback but, instead, by biasing decision making.

Abstract

Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of acoustic-phonetic mismatches in word forms. The source of TRACE's failure lay not in its interactive connectivity, not in the presence of interword competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model.

Abstract

Lexical knowledge influences how human listeners make decisions about speech sounds. Positive lexical effects (faster responses to target sounds in words than in nonwords) are robust across several laboratory tasks, while negative effects (slower responses to targets in more word-like nonwords than in less word-like nonwords) have been found in phonetic decision tasks but not phoneme monitoring tasks. The present experiments tested whether negative lexical effects are therefore a task-specific consequence of the forced choice required in phonetic decision. We compared phoneme monitoring and phonetic decision performance using the same Dutch materials in each task. In both experiments there were positive lexical effects, but no negative lexical effects. We observe that in all studies showing negative lexical effects, the materials were made by cross-splicing, which meant that they contained perceptual evidence supporting the lexically-consistent phonemes. Lexical knowledge seems to influence phonemic decision-making only when there is evidence for the lexically-consistent phoneme in the speech signal.

Abstract

We briefly describe the Merge model of phonemic decision-making, and, in the light of general arguments about the possible role of feedback in spoken-word recognition, defend Merge's feedforward structure. Merge not only accounts adequately for the data, without invoking feedback connections, but does so in a parsimonious manner.

Abstract

The central thesis of the target article was that feedback is never necessary in spoken word recognition. The commentaries present no new data and no new theoretical arguments which lead us to revise this position. In this response we begin by clarifying some terminological issues which have lead to a number of significant misunderstandings. We provide some new arguments to support our case that the feedforward model Merge is indeed more parsimonious than the interactive alternatives, and that it provides a more convincing account of the data than alternative models. Finally, we extend the arguments to deal with new issues raised by the commentators such as infant speech perception and neural architecture.

Abstract

Top-down feedback does not benefit speech recognition; on the contrary, it can hinder it. No experimental data imply that feedback loops are required for speech recognition. Feedback is accordingly unnecessary and spoken word recognition is modular. To defend this thesis, we analyse lexical involvement in phonemic decision making. TRACE (McClelland & Elman 1986), a model with feedback from the lexicon to prelexical processes, is unable to account for all the available data on phonemic decision making. The modular Race model (Cutler & Norris 1979) is likewise challenged by some recent results, however. We therefore present a new modular model of phonemic decision making, the Merge model. In Merge, information flows from prelexical processes to the lexicon without feedback. Because phonemic decisions are based on the merging of prelexical and lexical information, Merge correctly predicts lexical involvement in phonemic decisions in both words and nonwords. Computer simulations show how Merge is able to account for the data through a process of competition between lexical hypotheses. We discuss the issue of feedback in other areas of language processing and conclude that modular models are particularly well suited to the problems and constraints of speech recognition.

Abstract

Two word-spotting experiments are reported that examine whether the Possible-Word Constraint (PWC) [1] is a language-specific or language-universal strategy for the segmentation of continuous speech. The PWC disfavours parses which leave an impossible residue between the end of a candidate word and a known boundary. The experiments examined cases where the residue was either a CV syllable with a lax vowel, or a CVC syllable with a schwa. Although neither syllable context is a possible word in English, word-spotting in both contexts was easier than with a context consisting of a single consonant. The PWC appears to be language-universal rather than language-specific.

Abstract

Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of subcategorical mismatch in word forms. The source of TRACE's failure lay not in interactive connectivity, not in the presence of inter-word competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model, which has inter-word competition, phonemic representations and continuous optimisation (but no interactive connectivity).

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.