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

Magnuson, McMurray, Tanenhaus, and Aslin [Cogn. Sci. 27 (2003) 285] suggest that they have evidence of lexical feedback in speech perception, and that this evidence thus challenges the purely feedforward Merge model [Behav. Brain Sci. 23 (2000) 299]. This evidence is open to an alternative explanation, however, one which preserves the assumption in Merge that there is no lexical-prelexical feedback during on-line speech processing. This explanation invokes the distinction between perceptual processing that occurs in the short term, as an utterance is heard, and processing that occurs over the longer term, for perceptual learning.

Abstract

Spoken word recognition consists of two major component processes. First, at the prelexical stage, an abstract description of the utterance is generated from the information in the speech signal. Second, at the lexical stage, this description is used to activate all the words stored in the mental lexicon which match the input. These multiple candidate words then compete with each other. We review evidence which suggests that positive (match) and negative (mismatch) information of both a segmental and a suprasegmental nature is used to constrain this activation and competition process. We then ask whether, in addition to the necessary influence of the prelexical stage on the lexical stage, there is also feedback from the lexicon to the prelexical level. In two phonetic categorization experiments, Dutch listeners were asked to label both syllable-initial and syllable-final ambiguous fricatives (e.g., sounds ranging from [f] to [s]) in the word–nonword series maf–mas, and the nonword–word series jaf–jas. They tended to label the sounds in a lexically consistent manner (i.e., consistent with the word endpoints of the series). These lexical effects became smaller in listeners’ slower responses, even when the listeners were put under pressure to respond as fast as possible. Our results challenge models of spoken word recognition in which feedback modulates the prelexical analysis of the component sounds of a word whenever that word is heard

Abstract

This study demonstrates that listeners use lexical knowledge in perceptual learning of speech sounds. Dutch listeners first made lexical decisions on Dutch words and nonwords. The final fricative of 20 critical words had been replaced by an ambiguous sound, between [f] and [s]. One group of listeners heard ambiguous [f]-final words (e.g., [WI tlo?], from witlof, chicory) and unambiguous [s]-final words (e.g., naaldbos, pine forest). Another group heard the reverse (e.g., ambiguous [na:ldbo?], unambiguous witlof). Listeners who had heard [?] in [f]-final words were subsequently more likely to categorize ambiguous sounds on an [f]–[s] continuum as [f] than those who heard [?] in [s]-final words. Control conditions ruled out alternative explanations based on selective adaptation and contrast. Lexical information can thus be used to train categorization of speech. This use of lexical information differs from the on-line lexical feedback embodied in interactive models of speech perception. In contrast to on-line feedback, lexical feedback for learning is of benefit to spoken word recognition (e.g., in adapting to a newly encountered dialect).

Abstract

Participants' eye movements were monitored as they heard sentences and saw four pictured objects on a computer screen. Participants were instructed to click on the object mentioned in the sentence. There were more transitory fixations to pictures representing monosyllabic words (e.g. ham) when the first syllable of the target word (e.g. hamster) had been replaced by a recording of the monosyllabic word than when it came from a different recording of the target word. This demonstrates that a phonemically identical sequence can contain cues that modulate its lexical interpretation. This effect was governed by the duration of the sequence, rather than by its origin (i.e. which type of word it came from). The longer the sequence, the more monosyllabic-word interpretations it generated. We argue that cues to lexical-embedding disambiguation, such as segmental lengthening, result from the realization of a prosodic boundary that often but not always follows monosyllabic words, and that lexical candidates whose word boundaries are aligned with prosodic boundaries are favored in the word-recognition process.

Abstract

We have recently developed a new model of human speech recognition, based on automatic speech recognition techniques [1]. The present paper has two goals. First, we show that the new model performs well in the recognition of lexically ambiguous input. These demonstrations suggest that the model is able to operate in the same optimal way as human listeners. Second, we discuss how to relate the behaviour of a recogniser, designed to discover the optimum path through a word lattice, to data from human listening experiments. We argue that this requires a metric that combines both path-based and word-based measures of recognition performance. The combined metric varies continuously as the input speech signal unfolds over time.

Abstract

We present the results of a large-scale study on speech perception, assessing the number and type of perceptual hypotheses which listeners entertain about possible phoneme sequences in their language. Dutch listeners were asked to identify gated fragments of all 1179 diphones of Dutch, providing a total of 488 520 phoneme categorizations. The results manifest orderly uptake of acoustic information in the signal. Differences across phonemes in the rate at which fully correct recognition was achieved arose as a result of whether or not potential confusions could occur with other phonemes of the language ~long with short vowels, affricates with their initial components, etc.!. These data can be used to improve models of how acoustic phonetic information is mapped onto the mental lexicon during speech comprehension.

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.