Comprehenders generate expectations about upcoming lexical items in language processing using various types of contextual information. However, a number of studies have shown that argument roles do not impact neural and behavioral prediction measures. Despite these robust findings, some prior studies have suggested that lexical prediction might be sensitive to argument roles in production tasks such as the cloze task or in comprehension tasks when additional time is available for prediction. This study demonstrates that both the task and additional time (...) for prediction independently influence lexical prediction using argument roles, via evidence from closely matched electroencephalogram (EEG) and speeded cloze experiments. In order to investigate the timing effect, our EEG experiment used maximally simple Japanese stimuli such as Bee-nom/acc sting, and it manipulated the time for prediction by changing the temporal interval between the context noun and the target verb without adding any further linguistic content. In order to investigate the task effect, we conducted a speeded cloze study that was matched with our EEG study both in terms of stimuli and the time available for prediction. We found that both the EEG study with additional time for prediction and the speeded cloze study with matched timing showed clear sensitivity to argument roles, while the EEG conditions with less time for prediction replicated the standard pattern of argument role insensitivity. Based on these findings, we propose that lexical prediction is initially insensitive to argument roles but a monitoring mechanism serially inhibits role-inappropriate candidates. This monitoring process operates quickly in production tasks, where it is important to quickly select a single candidate to produce, whereas it may operate more slowly in comprehension tasks, where multiple candidates can be maintained until a continuation is perceived. Computational simulations demonstrate that this mechanism can successfully explain the task and timing effects observed in our experiments. (shrink)

Mapping from acoustic signals to lexical representations is a complex process mediated by a number of different levels of representation. This paper reviews properties of the phonetic and phonological levels, and hypotheses about how category structure is represented at each of these levels, and evaluates these hypotheses in light of relevant electrophysiological studies of phonetics and phonology. The paper examines evidence for two alternative views of how infant phonetic representations develop into adult representations, a structure-changing view and a structure-adding view, (...) and suggests that each may be better suited to different kinds of phonetic categories. Electrophysiological results are beginning to provide information about phonological representations, but less is known about how the more abstract representations at this level could be coded in the brain. (shrink)

A picture agrees with reality or fails to agree; it is correct or incorrect, true or false. What does this agreement consist in, if not in the fact that what is evidence in these language games speaks for our proposition?. The purpose of this paper is to outline a constructivist account of the notion of sense and to indicate why such an account is to be preferred to that given by classical semantics.

van der Velde's & de Kamps's model encodes complex word-to-word relations in sentences but does not encode the hierarchical constituent structure of sentences, a fundamental property of most accounts of sentence structure. We summarize what is at stake and suggest two ways of incorporating constituency into the model.

A critical flaw in Branigan & Pickering's (B&P's) advocacy of structural priming is the absence of a theory of priming. This undermines their claims about the value of priming as a methodology. In contrast, acceptability judgments enable clearer inferences about structure. It is important to engage thoroughly with the logic behind different structural diagnostics.

Under the lens of Marr’s (levels of analysis, we critique and extend the authors’ two points about language models (LMs) and language processing: first, predicting upcoming linguistic information based on context is key to language processing, and second, that many advances in psycholinguistics would be impossible without LLMs. We also outline directions combining LLMs’ strengths with psycholinguistic models.