Publications

Abstract

Individual differences in using language are prevalent in our daily lives. Language skills are often assessed in vocational (predominantly written language) and diagnostic contexts. Not much is known, however, about individual differences in spoken language skills. The lack of research is in part due to the lack of suitable test instruments. We introduce the Individual Differences in Language Skills (IDLaS-NL) test battery, a set of 31 behavioural tests that can be used to capture variability in language and relevant general cognitive skills in adult speakers of Dutch. The battery was designed to measure word and sentence production and comprehension skills, linguistic knowledge, nonverbal processing speed, working memory, and nonverbal reasoning. The present article outlines the structure of the battery, describes the materials and procedure of each test, and evaluates the battery’s factor structure based on the results of a sample of 748 Dutch adults, aged between 18 and 30 years, most of them students. The analyses demonstrate that the battery has good construct validity and can be reliably administered both in the lab and via the internet. We therefore recommend the battery as a valuable new tool to assess individual differences in language knowledge and skills; this future work may include linking language skills to other aspects of human cognition and life outcomes.

Abstract

In reply to Magnuson, Crinnion, Luthra, Gaston, and Grubb (2023), we challenge their conclusion that on-line activation feedback improves word recognition. This type of feedback is instantiated in the TRACE model (McClelland & Elman, 1986) as top-down spread of activation from lexical to phoneme nodes. We give two main reasons why Magnuson et al.'s demonstration that activation feedback speeds up word recognition in TRACE is not informative about whether activation feedback helps humans recognize words. First, the same speed-up could be achieved by changing other parameters in TRACE. Second, more fundamentally, there is room for improvement in TRACE's performance only because the model, unlike Bayesian models, is suboptimal. We also challenge Magnuson et al.'s claim that the available empirical data support activation feedback. The data they base this claim on are open to alternative explanations and there are data against activation feedback that they do not discuss. We argue, therefore, that there are no computational or empirical grounds to conclude that activation feedback benefits human spoken-word recognition and indeed no theoretical grounds why activation feedback would exist. Other types of feedback, for example feedback to support perceptual learning, likely do exist, precisely because they can help listeners recognize words.

Abstract

We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training explicitly defined a voice-identity space. The predefined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training histories on different tests. Cortical sensitivity to voice similarity appeared over different time-scales and at different representational stages. First, there were short-term adaptation effects: Increasing acoustic similarity to the directly preceding stimulus led to haemodynamic response reduction in the middle/posterior STS and in right ventrolateral prefrontal regions. Second, there were longer-term effects: Response reduction was found in the orbital/insular cortex for stimuli that were most versus least similar to the acoustic mean of all preceding stimuli, and, in the anterior temporal pole, the deep posterior STS and the amygdala, for stimuli that were most versus least similar to the trained voice-identity category mean. These findings are interpreted as effects of neural sharpening of long-term stored typical acoustic and category-internal values. The analyses also reveal anatomically separable voice representations: one in a voice-acoustics space and one in a voice-identity space. Voice-identity representations flexibly followed the trained identity shift, and listeners with a greater identity effect were more accurate at recognizing familiar voices. Voice recognition is thus supported by neural voice spaces that are organized around flexible ‘mean voice’ representations.

Abstract

The possible-word constraint (PWC; Norris, McQueen, Cutler, & Butterfield, 1997) has been proposed as a language-universal segmentation principle: Lexical candidates are disfavoured if the resulting segmentation of continuous speech leads to vowelless residues in the input—for example, single consonants. Three word-spotting experiments investigated segmentation in Slovak, a language with single-consonant words and fixed stress. In Experiment 1, Slovak listeners detected real words such as ruka “hand” embedded in prepositional-consonant contexts (e.g., /gruka/) faster than those in nonprepositional-consonant contexts (e.g., /truka/) and slowest in syllable contexts (e.g., /dugruka/). The second experiment controlled for effects of stress. Responses were still fastest in prepositional-consonant contexts, but were now slowest in nonprepositional-consonant contexts. In Experiment 3, the lexical and syllabic status of the contexts was manipulated. Responses were again slowest in nonprepositional-consonant contexts but equally fast in prepositional-consonant, prepositional-vowel, and nonprepositional-vowel contexts. These results suggest that Slovak listeners use fixed stress and the PWC to segment speech, but that single consonants that can be words have a special status in Slovak segmentation. Knowledge about what constitutes a phonologically acceptable word in a given language therefore determines whether vowelless stretches of speech are or are not treated as acceptable parts of the lexical parse.

Abstract

Signed languages are articulated through simultaneous upper-body movements and are seen; spoken languages are articulated through sequential vocal-tract movements and are heard. But word recognition in both language modalities entails segmentation of a continuous input into discrete lexical units. According to the Possible Word Constraint (PWC), listeners segment speech so as to avoid impossible words in the input. We argue here that the PWC is a modality-general principle. Deaf signers of British Sign Language (BSL) spotted real BSL signs embedded in nonsense-sign contexts more easily when the nonsense signs were possible BSL signs than when they were not. A control experiment showed that there were no articulatory differences between the different contexts. A second control experiment on segmentation in spoken Dutch strengthened the claim that the main BSL result likely reflects the operation of a lexical-viability constraint. It appears that signed and spoken languages, in spite of radical input differences, are segmented so as to leave no residues of the input that cannot be words.

Abstract

Japanese listeners detected Japanese words embedded at the end of nonsense sequences (e.g., kaba 'hippopotamus' in gyachikaba). When the final portion of the preceding context together with the initial portion of the word (e.g., here, the sequence chika) was compatible with many lexical competitors, recognition of the embedded word was more difficult than when such a sequence was compatible with few competitors. This clear effect of competition, established here for preceding context in Japanese, joins similar demonstrations, in other languages and for following contexts, to underline that the functional architecture of the human spoken-word recognition system is a universal one.

Abstract

For optimal word recognition listeners should use all relevant acoustic information as soon as it comes available. Using printed-word eye-tracking we investigated when during word processing Dutch listeners use suprasegmental lexical stress information to recognize words. Fixations on targets such as 'OCtopus' (capitals indicate stress) were more frequent than fixations on segmentally overlapping but differently stressed competitors ('okTOber') before segmental information could disambiguate the words. Furthermore, prior to segmental disambiguation, initially stressed words were stronger lexical competitors than non-initially stressed words. Listeners recognize words by immediately using all relevant information in the speech signal.

Abstract

Four cross-modal repetition priming experiments examined whether consonant duration in Italian provides listeners with information not only for segmental identification ("what" information: whether the consonant is a geminate or a singleton) but also for lexical segmentation (“where” information: whether the consonant is in word-initial or word-medial position). Italian participants made visual lexical decisions to words containing geminates or singletons, preceded by spoken primes (whole words or fragments) containing either geminates or singletons. There were effects of segmental identity (geminates primed geminate recognition; singletons primed singleton recognition), and effects of consonant position (regression analyses revealed graded effects of geminate duration only for geminates which can vary in position, and mixed-effect modeling revealed a positional effect for singletons only in low-frequency words). Durational information appeared to be more important for segmental identification than for lexical segmentation. These findings nevertheless indicate that the same kind of information can serve both "what" and "where" functions in speech comprehension, and that the perceptual processes underlying those functions are interdependent.

Abstract

In foreign-accented speech, listeners have to handle noticeable deviations from the standard pronunciation of a target language. Three cross-modal priming experiments investigated how short- and long-term experiences with a foreign accent influence word recognition by native listeners. In experiment 1, German-accented words were presented to Dutch listeners who had either extensive or limited prior experience with German-accented Dutch. Accented words either contained a diphthong substitution that deviated acoustically quite largely from the canonical form (huis [hys], "house", pronounced as [hoys]), or that deviated acoustically to a lesser extent (lijst [lst], "list", pronounced as [lst]). The mispronunciations never created lexical ambiguity in Dutch. While long-term experience facilitated word recognition for both types of substitutions, limited experience facilitated recognition only of words with acoustically smaller deviations. In experiment 2, Dutch listeners with limited experience listened to the German speaker for 4 min before participating in the cross-modal priming experiment. The results showed that speaker-specific learning effects for acoustically large deviations can be obtained already after a brief exposure, as long as the exposure contains evidence of the deviations. Experiment 3 investigates whether these short-term adaptation effects for foreign-accented speech are speaker-independent.

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.