scholarly journals Toward Computational Models of Multilingual Sentence Processing

2020 ◽  
Author(s):  
Stefan L. Frank
Keyword(s):  
Sentence Processing ◽  
Computational Models

scholarly journals Computational Models of Retrieval Processes in Sentence Processing

2021 ◽  
Author(s):  
Shravan Vasishth ◽  
Bruno Nicenboim ◽  
Felix Engelmann ◽  
Frank Burchert
Keyword(s):  
Sentence Processing ◽  
Computational Models ◽  
Retrieval Processes

scholarly journals Towards computational models of multilingual sentence processing

2019 ◽  
Author(s):  
Stefan L. Frank
Keyword(s):  
Computational Linguistics ◽  
Sentence Processing ◽  
Computational Models ◽  
State Of The Art ◽  
Cognitive Models ◽  
The State ◽  
Cognitive Modelling ◽  
Current Review ◽  
Multiple Languages ◽  
Human Sentence Processing

Although computational models can simulate aspects of human sentence processing, research on this topic has remained almost exclusively limited to the single language case. The current review presents an overview of the state of the art in computational cognitive models of sentence processing, and discusses how recent sentence-processing models can be used to study bi- and multilingualism. Recent results from cognitive modelling and computational linguistics suggest that phenomena specific to bilingualism can emerge from systems that have no dedicated components for handling multiple languages. Hence, accounting for human bi-/multilingualism may not require models that are much more sophisticated than those for the monolingual case.

scholarly journals Computational models of retrieval processes in sentence processing

2019 ◽  
Author(s):  
Shravan Vasishth ◽  
Bruno Nicenboim ◽  
Felix Engelmann ◽  
Frank Burchert
Keyword(s):  
Sentence Processing ◽  
Sentence Comprehension ◽  
Computational Models ◽  
Predictive Performance ◽  
Data Set ◽  
Benchmark Data ◽  
Retrieval Processes ◽  
Empirical Coverage ◽  
Competing Models ◽  
Retrieval From Memory

Sentence comprehension requires that the comprehender work out who did what to whom. This process has been characterized as retrieval from memory. This review summarizes the quantitative predictions and empirical coverage of the two existing computational models of retrieval, and shows how the predictive performance of these two competing models can be tested against a benchmark data-set. We also show how computational modeling can help us better understand sources of variability in both unimpaired and impaired sentence comprehension.

Computational Models of Reading

2021 ◽  
Author(s):  
Erik D. Reichle
Keyword(s):  
Sentence Processing ◽  
Visual Processing ◽  
Computational Models ◽  
Word Identification ◽  
Movement Control ◽  
Theoretical Work ◽  
Computer Models ◽  
Reading Processes ◽  
Core Reading ◽  
Models Of Reading

This book describes computational models of reading, or models that simulate and explain the mental processes that support the reading of text. The book provides introductory chapters on both reading research and computer models. The central chapters of the book then review what has been learned about reading from empirical research on four core reading processes: word identification, sentence processing, discourse representation, and how these three processes are coordinated with visual processing, attention, and eye-movement control. These central chapters also review an influential sample of computer models that have been developed to explain these key empirical findings, as well as comparative analyses of those models. The final chapter attempts to integrate this empirical and theoretical work by both describing a new comprehensive model of reading, Über-Reader, and reporting several simulations to illustrate how the model accounts for many of the basic phenomena related to reading.

scholarly journals Computational Models of Retrieval Processes in Sentence Processing

2019 ◽  
Vol 23 (11) ◽  
pp. 968-982 ◽  
Author(s):  
Shravan Vasishth ◽  
Bruno Nicenboim ◽  
Felix Engelmann ◽  
Frank Burchert
Keyword(s):  
Sentence Processing ◽  
Computational Models ◽  
Retrieval Processes

scholarly journals Individual differences in cue-weighting in sentence comprehension: An evaluation using Approximate Bayesian Computation

2021 ◽  
Author(s):  
Himanshu Yadav ◽  
Dario Paape ◽  
Garrett Smith ◽  
Brian Dillon ◽  
Shravan Vasishth
Keyword(s):  
Individual Differences ◽  
Sentence Processing ◽  
Sentence Comprehension ◽  
Computational Models ◽  
Approximate Bayesian Computation ◽  
Reading Proficiency ◽  
Bayesian Computation ◽  
Individual Level ◽  
Cue Weighting ◽  
Approximate Bayesian

Cue-based retrieval theories of sentence processing assume that syntactic dependencies are resolved through a content-addressable search process. An important recent claim is that in certain dependency types, the retrieval cues are weighted such that one cue dominates. This cue-weighting proposal aims to explain the observed average behavior, but here we show that there is systematic individual-level variation in cue weighting. Using the Lewis and Vasishth cue-based retrieval model, we estimated individual-level parameters for processing speed and cue weighting using 13 published datasets; hierarchical Approximate Bayesian Computation (ABC) was used to estimate the parameters. The modeling reveals a nuanced picture of cue weighting: we find support for the idea that some participants weight cues differentially, but not all participants do. Only fast readers tend to have the higher weighting for structural cues, suggesting that reading proficiency might be associated with cue weighting. A broader achievement of the work is to demonstrate how individual differences can be investigated in computational models of sentence processing without compromising the complexity of the model.

scholarly journals Sentence Comprehension as a Cognitive Process

2021 ◽  
Author(s):  
Shravan Vasishth ◽  
Felix Engelmann
Keyword(s):  
Computational Linguistics ◽  
Sentence Processing ◽  
Cognitive Processes ◽  
Cognitive Process ◽  
Sentence Comprehension ◽  
Computational Models ◽  
Model Comparison ◽  
Written Language ◽  
Retrieval Processes ◽  
New Research

Sentence comprehension - the way we process and understand spoken and written language - is a central and important area of research within psycholinguistics. This book explores the contribution of computational linguistics to the field, showing how computational models of sentence processing can help scientists in their investigation of human cognitive processes. It presents the leading computational model of retrieval processes in sentence processing, the Lewis and Vasishth cue-based retrieval mode, and develops a principled methodology for parameter estimation and model comparison/evaluation using benchmark data, to enable researchers to test their own models of retrieval against the present model. It also provides readers with an overview of the last 20 years of research on the topic of retrieval processes in sentence comprehension, along with source code that allows researchers to extend the model and carry out new research. Comprehensive in its scope, this book is essential reading for researchers in cognitive science.

When Hearing Does Not Mean Understanding: On the Neural Processing of Syntactically Complex Sentences by Listeners With Hearing Loss

2021 ◽  
pp. 1-13
Author(s):  
Margreet Vogelzang ◽  
Christiane M. Thiel ◽  
Stephanie Rosemann ◽  
Jochem W. Rieger ◽  
Esther Ruigendijk
Keyword(s):  
Hearing Loss ◽  
Sentence Processing ◽  
Secondary Task ◽  
Sentence Comprehension ◽  
Inferior Frontal Gyrus ◽  
Normal Hearing ◽  
Cognitive Demands ◽  
Sentence Complexity ◽  
Complex Sentences ◽  
And Task

Purpose Adults with mild-to-moderate age-related hearing loss typically exhibit issues with speech understanding, but their processing of syntactically complex sentences is not well understood. We test the hypothesis that listeners with hearing loss' difficulties with comprehension and processing of syntactically complex sentences are due to the processing of degraded input interfering with the successful processing of complex sentences. Method We performed a neuroimaging study with a sentence comprehension task, varying sentence complexity (through subject–object order and verb–arguments order) and cognitive demands (presence or absence of a secondary task) within subjects. Groups of older subjects with hearing loss ( n = 20) and age-matched normal-hearing controls ( n = 20) were tested. Results The comprehension data show effects of syntactic complexity and hearing ability, with normal-hearing controls outperforming listeners with hearing loss, seemingly more so on syntactically complex sentences. The secondary task did not influence off-line comprehension. The imaging data show effects of group, sentence complexity, and task, with listeners with hearing loss showing decreased activation in typical speech processing areas, such as the inferior frontal gyrus and superior temporal gyrus. No interactions between group, sentence complexity, and task were found in the neuroimaging data. Conclusions The results suggest that listeners with hearing loss process speech differently from their normal-hearing peers, possibly due to the increased demands of processing degraded auditory input. Increased cognitive demands by means of a secondary visual shape processing task influence neural sentence processing, but no evidence was found that it does so in a different way for listeners with hearing loss and normal-hearing listeners.

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