scholarly journals Word predictability effects are linear, not logarithmic: Implications for probabilistic models of sentence comprehension

2021 ◽  
Vol 116 ◽  
pp. 104174
Author(s):  
Trevor Brothers ◽  
Gina R. Kuperberg
Keyword(s):  
Sentence Comprehension ◽  
Probabilistic Models ◽  
Word Predictability

scholarly journals The interaction between structure and meaning in sentence comprehension: Recurrent neural networks and reading times

2019 ◽  
Author(s):  
Stefan L. Frank ◽  
John Hoeks
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Sentence Processing ◽  
Recurrent Neural Networks ◽  
Sentence Comprehension ◽  
Semantic Relations ◽  
Garden Path ◽  
Word Predictability ◽  
Syntactic Ambiguities ◽  
Potential Object

Recurrent neural network (RNN) models of sentence processing have recently displayed a remarkable ability to learn aspects of structure comprehension, as evidenced by their ability to account for reading times on sentences with local syntactic ambiguities (i.e., garden-path effects). Here, we investigate if these models can also simulate the effect of semantic appropriateness of the ambiguity's readings. RNNs-based estimates of surprisal of the disambiguating verb of sentences with an NP/S-coordination ambiguity (as in `The wizard guards the king and the princess protects ...') show identical patters to human reading times on the same sentences: Surprisal is higher on ambiguous structures than on their disambiguated counterparts and this effect is weaker, but not absent, in cases of poor thematic fit between the verb and its potential object (`The teacher baked the cake and the baker made ...'). These results show that an RNN is able to simultaneously learn about structural and semantic relations between words and suggest that garden-path phenomena may be more closely related to word predictability than traditionally assumed.

scholarly journals Parsing costs as predictors of reading difficulty: An evaluation using the Potsdam Sentence Corpus

2008 ◽  
Vol 2 (1) ◽  
Author(s):  
Marisa Ferrara Boston ◽  
John Hale ◽  
Reinhold Kliegl ◽  
Umesh Patil ◽  
Shravan Vasishth
Keyword(s):  
Sentence Comprehension ◽  
Bigram Frequency ◽  
Syntactic Parsing ◽  
Linear Mixed Effects Model ◽  
Linear Mixed Effects ◽  
Comprehension Difficulty ◽  
Fixation Durations ◽  
Word Predictability ◽  
Processing Difficulty ◽  
Models Of Reading

The surprisal of a word on a probabilistic grammar constitutes a promising complexity metric for human sentence comprehension difficulty. Using two different grammar types, surprisal is shown to have an effect on fixation durations and regression probabilities in a sample of German readers’ eye movements, the Potsdam Sentence Corpus. A linear mixed-effects model was used to quantify the effect of surprisal while taking into account unigram frequency and bigram frequency (transitional probability), word length, and empirically-derived word predictability; the socalled “early” and “late” measures of processing difficulty both showed an effect of surprisal. Surprisal is also shown to have a small but statistically non-significant effect on empirically-derived predictability itself. This work thus demonstrates the importance of including parsing costs as a predictor of comprehension difficulty in models of reading, and suggests that a simple identification of syntactic parsing costs with early measures and late measures with durations of post-syntactic events may be difficult to uphold.

scholarly journals Acquiring L2 sentence comprehension: A longitudinal study of word monitoring in noise

2012 ◽  
Vol 15 (4) ◽  
pp. 841-857 ◽  
Author(s):  
GEORGINA OLIVER ◽  
MARIANNE GULLBERG ◽  
FRAUKE HELLWIG ◽  
HOLGER MITTERER ◽  
PETER INDEFREY
Keyword(s):  
Phonological Processing ◽  
Auditory Processing ◽  
Semantic Processing ◽  
Sentence Comprehension ◽  
Native Speakers ◽  
Word Predictability ◽  
L2 Listening ◽  
Semantic Transfer ◽  
Different Levels ◽  
Observation Period

This study investigated the development of second language online auditory processing with ab initio German learners of Dutch. We assessed the influence of different levels of background noise and different levels of semantic and syntactic target word predictability on word-monitoring latencies. There was evidence of syntactic, but not lexical-semantic, transfer from the L1 to the L2 from the onset of L2 learning. An initial stronger adverse effect of noise on syntactic compared to phonological processing disappeared after two weeks of learning Dutch suggesting a change towards more robust syntactic processing. At the same time the L2 learners started to exploit semantic constraints predicting upcoming target words. The use of semantic predictability remained less efficient compared to native speakers until the end of the observation period. The improvement and the persistent problems in semantic processing we found were independent of noise and rather seem to reflect the need for more context information to build up online semantic representations in L2 listening.

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.

Distance effect on sentence comprehension in French language

2011 ◽  
Author(s):  
K. Takahashi ◽  
N. Maionchi-Pino ◽  
A. Magnan ◽  
R. Kawashima
Keyword(s):  
Sentence Comprehension ◽  
Distance Effect ◽  
French Language

Management of Economics and State "Bottom"

2020 ◽  
Vol 17 (6) ◽  
pp. 76-91
Author(s):  
E. D. Solozhentsev
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Probabilistic Models ◽  
Human Life ◽  
Special Software ◽  
Human Quality ◽  
Relationship Of ◽  
The Relationship

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.

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