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Chukharev-Hudilainen, Evgeny; Ockey, Gary J. – ETS Research Report Series, 2021
This paper describes the development and evaluation of Interaction Competence Elicitor (ICE), a spoken dialog system (SDS) for the delivery of a paired oral discussion task in the context of language assessment. The purpose of ICE is to sustain a topic-specific conversation with a test taker in order to elicit discourse that can be later judged to…
Descriptors: Intercultural Communication, Oral Language, Communicative Competence (Languages), Error Analysis (Language)
Akbari, Alireza – International Journal of Education and Literacy Studies, 2014
The petition for language translation has strikingly augmented recently due to cross-cultural communication and exchange of information. In order to communicate well, text should be translated correctly and completely in each field such as legal documents, technical texts, scientific texts, publicity leaflets, and instructional materials. In this…
Descriptors: Translation, Computational Linguistics, Models, Accuracy
Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel – Computer Assisted Language Learning, 2016
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
Descriptors: Discourse Analysis, Feedback (Response), Undergraduate Students, Accuracy
Garnier, Marie – Research-publishing.net, 2012
According to recent studies, there is a persistence of adverb placement errors in the written productions of francophone learners and users of English at an intermediate to advanced level. In this paper, we present strategies for the automatic detection and correction of errors in the placement of manner adverbs, using linguistic-based natural…
Descriptors: Form Classes (Languages), Error Correction, Natural Language Processing, Feedback (Response)
Hudson Kam, Carla L.; Newport, Elissa L. – Cognitive Psychology, 2009
When natural language input contains grammatical forms that are used probabilistically and inconsistently, learners will sometimes reproduce the inconsistencies; but sometimes they will instead regularize the use of these forms, introducing consistency in the language that was not present in the input. In this paper we ask what produces such…
Descriptors: Form Classes (Languages), Artificial Languages, Adult Learning, Linguistic Input