scholarly journals Examining Working Memory during Sentence Construction with an ACT-R Model of Grammatical Encoding

2017 ◽  
Author(s):  
Jeremy Cole ◽  
David Reitter
Keyword(s):  
Working Memory ◽  
Language Production ◽  
Categorial Grammar ◽  
Grammatical Encoding ◽  
Sentence Complexity ◽  
Human Data ◽  
Combinatory Categorial Grammar ◽  
Sentence Construction ◽  
Incremental Strategy

We examine working memory use and incrementality using acognitive model of grammatical encoding. Our model combinesan empirically validated framework, ACT-R, with a linguistictheory, Combinatory Categorial Grammar, to target thatphase of language production. By building the model with theSwitchboard corpus, it can attempt to realize a larger set ofsentences. With this methodology, different strategies may becompared according to the similarity of the model’s sentencesto the test sentences. In this way, the model can still be evaluatedby its fit to human data, without overfitting to individualexperiments. The results show that while having more workingmemory available improves performance, using less workingmemory during realization is correlated with a closer fit,even after controlling for sentence complexity. Further, sentencesrealized with a more incremental strategy are also moresimilar to the corpus sentences as measured by edit distance.As high incrementality is correlated with low working memoryusage, this study offers a possible mechanism by whichincrementality can be explained.

scholarly journals A Case of a Monolingual Spanish-Speaking Latina with Semantic Variant Primary Progressive Aphasia (svPPA)

2019 ◽  
Vol 34 (7) ◽  
pp. 1290-1290
Author(s):  
L Perez
Keyword(s):  
Working Memory ◽  
Language Production ◽  
Primary Progressive Aphasia ◽  
Motor Speech ◽  
Problem Solving Skills ◽  
Progressive Aphasia ◽  
Primary Progressive ◽  
Spanish Speaking ◽  
Word Finding ◽  
Semantic Variant

Abstract Objective Often, individuals with lower educational attainment and limited proficiency in the English language get misdiagnosed and/or undertreated, which can impact their quality of life and other outcomes. The present case study intends to review and discuss the presentation of a monolingual, Spanish-speaking woman with Semantic Variant Primary Progressive Aphasia (svPPA), who was originally referred for a neuropsychological evaluation to determine the severity of her existing Alzheimer’s Disease (AD) diagnosis. Case Description Ms. X, is a 64-year-old, right-handed Hispanic woman with 6 years of education. Symptoms included forgetfulness, restlessness, and insomnia. Her family reported that she was repeating her ideas frequently during conversations and failing to recognize previously acquainted people, including her own relatives. A recent MRI of the brain showed anterior temporal lobe atrophy. Diagnostic Impressions and Outcomes Overall, she showed naming deficits (anomia), impaired verbal fluency, surface dyslexia, and significant problems with comprehension. Executive functioning, sentence repetition, working memory, and attention were generally intact. Qualitatively, her speech was apparently fluent and automatic, yet clearly empty in meaning. In Ms. X’s case, collateral reports of word-finding difficulties, tendency to repeat her thoughts incessantly, associative agnosia and prosopagnosia, and spared repetition and motor speech are strongly indicative of svPPA. Discussion svPPA primarily impacts language production and comprehension, and is characterized by severe anomia, word-finding difficulties, impaired single word comprehension, and in some cases, defective recognition of familiar faces. On testing, impairments can be observed in confrontation naming, with motor speech and repetition, working memory, episodic memory, visuospatial skills, and problem-solving skills relatively intact. Language symptoms are thought to stem from deficits of the semantic system.

scholarly journals The Relationship between Executive Functions and Language Production in 5–6-Year-Old Children: Insights from Working Memory and Storytelling

2020 ◽  
Vol 10 (2) ◽  
pp. 52
Author(s):  
Aleksander Veraksa ◽  
Daria Bukhalenkova ◽  
Natalia Kartushina ◽  
Ekaterina Oshchepkova
Keyword(s):  
Working Memory ◽  
Language Production ◽  
Working Memory Capacity ◽  
Narrative Structure ◽  
Verbal Working Memory ◽  
Memory Capacity ◽  
Story Retelling ◽  
Grammatical Accuracy ◽  
The Relationship ◽  
Global Indicators

This study examined the relationship between working memory capacity and narrative abilities in 5–6-year-old children. 269 children were assessed on their visual and verbal working memory and performed in a story retelling and a story creation (based on a single picture and on a series of pictures) tasks. The stories were evaluated on their macrostructure and microstructure. The results revealed a significant relationship between both components (verbal and visual) of working memory and the global indicators of a story’s macrostructure—such as semantic completeness, semantic adequacy, programming and narrative structure—and with the indicators of a story’s microstructure, such as grammatical accuracy and number of syntagmas. Yet, this relationship was systematically stronger for verbal working memory, as compared to visual working memory, suggesting that a well-developed verbal working memory leads to lexically and grammatically more accurate language production in preschool children.

scholarly journals CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank

2007 ◽  
Vol 33 (3) ◽  
pp. 355-396 ◽  
Author(s):  
Julia Hockenmaier ◽  
Mark Steedman
Keyword(s):  
Long Range ◽  
State Of The Art ◽  
Categorial Grammar ◽  
Linguistic Data ◽  
Combinatory Categorial Grammar ◽  
Extensive Analysis ◽  
Dependency Structures

This article presents an algorithm for translating the Penn Treebank into a corpus of Combinatory Categorial Grammar (CCG) derivations augmented with local and long-range word-word dependencies. The resulting corpus, CCGbank, includes 99.4% of the sentences in the Penn Treebank. It is available from the Linguistic Data Consortium, and has been used to train wide-coverage statistical parsers that obtain state-of-the-art rates of dependency recovery. In order to obtain linguistically adequate CCG analyses, and to eliminate noise and inconsistencies in the original annotation, an extensive analysis of the constructions and annotations in the Penn Treebank was called for, and a substantial number of changes to the Treebank were necessary. We discuss the implications of our findings for the extraction of other linguistically expressive grammars from the Treebank, and for the design of future treebanks.

Sign in / Sign up

Export Citation Format

Share Document