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Salem, Alexandra C.; Gale, Robert; Casilio, Marianne; Fleegle, Mikala; Fergadiotis, Gerasimos; Bedrick, Steven – Journal of Speech, Language, and Hearing Research, 2023
Purpose: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for…
Descriptors: Semantics, Computer Software, Aphasia, Classification
Dadang Sudana; Tri Indri Hardini; Mahardhika Zifana – International Journal of Language Education, 2024
A tension exists between rationalists and empiricists regarding the nature of knowledge: innate then activated/discovered (rationalists) or constructed then invented (empiricists). The assumption is that, to a certain extent, basic knowledge seems to be innate in our mind and develops through experience by thinking processes to construct meanings.…
Descriptors: Indonesian, Verbs, Teaching Methods, Semantics
Mengliyev, Bakhtiyor; Shahabitdinova, Shohida; Khamroeva, Shahlo; Gulyamova, Shakhnoza; Botirova, Adiba – Journal of Language and Linguistic Studies, 2021
This article is dedicated to the issue of morphological analysis and synthesis of word forms in a linguistic analyzer, which is a significant feature of corpus linguistics. The article discourses in detail the morphological analysis, the creation of artificial language, grammar and analyzer, the general scheme of the analysis program that…
Descriptors: Morphology (Languages), Computational Linguistics, Computer Software, Artificial Languages
Patience Stevens; David Plaut – Grantee Submission, 2020
The statistical structure of a given language likely drives our sensitivity to words' morphological structure. The current work begins to investigate to what degree morphological processing effects observed in visual word recognition can be attributed to statistical regularities between orthography and semantics in English, without any prior…
Descriptors: Reading Processes, Word Recognition, Semantics, Written Language
Eun Seon Chung – Language Learning & Technology, 2024
While previous investigations on online machine translation (MT) in language learning have analyzed how second language (L2) learners use and post-edit MT output, no study as of yet has investigated how the learners process MT errors and what factors affect this process using response and reading times. The present study thus investigates L2…
Descriptors: English (Second Language), Korean, Language Processing, Translation
Ferman, Sara; Shmuel, Sapir Amira; Zaltz, Yael – Language Learning and Development, 2022
The acquisition of a new morphological rule can be influenced by numerous factors, including the type of feedback provided during learning. The present study aimed to test the effect of different feedback types on children's ability to learn and generalize an artificial morphological rule (AMR). Two groups of eight-year-olds learned to judge and…
Descriptors: Morphology (Languages), Feedback (Response), Error Correction, Learning Processes
Keezhatta, Muhammed Salim – Arab World English Journal, 2019
Natural Language Processing (NLP) platforms have recently reported a higher adoption rate of Artificial Intelligence (AI) applications. The purpose of this research is to examine the relationship between NLP and AI in the application of linguistic tasks related to morphology, parsing, and semantics. To achieve this objective, a theoretical…
Descriptors: Models, Correlation, Natural Language Processing, Artificial Intelligence
Eggleston, Keri M. – ProQuest LLC, 2013
The Tlingit language, indigenous to Southeast Alaska and neighboring parts of British Columbia and the Yukon territory, is related to the Athabascan languages and the recently extinct language Eyak. Like Athabascan and Eyak, Tlingit verbal morphology is highly complex. The conjugation of Tlingit verbs is unpredictable in certain respects, making…
Descriptors: American Indian Languages, Foreign Countries, Verbs, Morphology (Languages)
Garnier, Marie – European Association for Computer-Assisted Language Learning (EUROCALL), 2012
This article presents the preliminary steps to the implementation of detection and correction strategies for the erroneous use of N+N structures in the written productions of French-speaking advanced users of English. This research is carried out as part of the grammar checking project "CorrecTools", in which errors are detected and corrected…
Descriptors: Error Correction, Language Research, English (Second Language), French
Peer reviewedGay, L. S.; Croft, W. B. – Information Processing and Management, 1990
Discusses the interpretation of nominal compounds in the context of natural language processing for information retrieval. Knowledge-intensive algorithms that can successfully interpret compounds found in technical documents are described, and experiments are reported that indicate these algorithms may be unnecessary for improving retrieval…
Descriptors: Algorithms, Computer Software, Information Retrieval, Morphology (Languages)
Peer reviewedLevison, Michael; Lessard, Greg – Computer Assisted Language Learning, 1996
Describes a language generation system, which, given data files describing a natural language, generates utterances of the class the user has specified. The system can exercise control over the syntax, lexicon, morphology, and semantics of the language. This article explores a range of the system's potential applications to second-language…
Descriptors: Computer Assisted Instruction, Computer Software, Error Analysis (Language), Learning Strategies
Hutchins, Sandra E. – 1985
By analyzing the lexicology of natural language (English or other languages as they are commonly spoken or written), as compared to computer languages, this study explored the extent to which syntactic and semantic levels of linguistic analysis can be implemented and effectively used on microcomputers. In Phase I of the study, the Apple IIe with…
Descriptors: Componential Analysis, Computer Software, Factor Analysis, Human Resources

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