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Jie Zhang – International Journal of Information and Communication Technology Education, 2024
This paper explores the development of an intelligent translation system for spoken English using Recurrent Neural Network (RNN) models. The fundamental principles of RNNs and their advantages in processing sequential data, particularly in handling time-dependent natural language data, are discussed. The methodology for constructing the…
Descriptors: Oral Language, Translation, Computational Linguistics, Computer Software
Masaki Eguchi – Vocabulary Learning and Instruction, 2022
Building on previous studies investigating the multidimensional nature of lexical use in task-based L2 performance, this study clarified the roles that the distinct lexical features play in predicting vocabulary proficiency in a corpus of L2 Oral Proficiency Interviews (OPI). A total of 85 OPI samples were rated by three separate raters based on a…
Descriptors: Lexicology, Oral Language, Language Proficiency, Vocabulary Development
Tzu-Yu Tai – Computer Assisted Language Learning, 2024
Intelligent personal assistants (IPAs) are a valuable tool in language learning because they provide opportunities for authentic interaction. However, their effectiveness, compared with that of human interlocutors, in facilitating second and foreign language interaction has not been explored. Therefore, this study investigated the effect of IPAs…
Descriptors: Artificial Intelligence, Natural Language Processing, English (Second Language), Second Language Learning
Bosker, Hans Rutger; Badaya, Esperanza; Corley, Martin – Discourse Processes: A Multidisciplinary Journal, 2021
Speech in everyday conversations is riddled with discourse markers (DMs), such as "well," "you know," and "like." However, in many lab-based studies of speech comprehension, such DMs are typically absent from the carefully articulated and highly controlled speech stimuli. As such, little is known about how these DMs…
Descriptors: Discourse Analysis, Language Usage, Word Recognition, Eye Movements
Nie, Bruce; Deacon, Hélène; Fyshe, Alona; Epp, Carrie Demmans – International Educational Data Mining Society, 2022
A child's ability to understand text (reading comprehension) can greatly impact both their ability to learn in the classroom and their future contributions to society. Reading comprehension draws on oral language; behavioural measures of knowledge at the word and sentence levels have been shown to be related to children's reading comprehension. In…
Descriptors: Reading Comprehension, Word Order, Sentence Structure, Grade 3
Eguchi, Masaki; Kyle, Kristopher – Modern Language Journal, 2020
Lexical sophistication has been an important indicator of productive lexical proficiency for almost 30 years. Although lexical sophistication has most often been operationalized as the proportion of low frequency words in a text, a growing body of research has indicated that a number of indices such as concreteness, hypernymy, and n-gram…
Descriptors: Oral Language, Language Proficiency, Lexicology, English Language Learners
Haerim Hwang; Hyunwoo Kim – Language Testing, 2024
Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides…
Descriptors: Korean, Natural Language Processing, Syntax, Computer Graphics
Hunte, Melissa R.; McCormick, Samantha; Shah, Maitree; Lau, Clarissa; Jang, Eunice Eunhee – Assessment in Education: Principles, Policy & Practice, 2021
Children's oral language proficiency (OLP) is integral for developing literacy skills. Storytelling or retelling is often used by parents and educators to elicit children's OLP, yet it is less commonly used for assessment purposes. Leveraged by natural language processing and machine learning, this study examined the extent to which computational…
Descriptors: Scores, Natural Language Processing, Oral Language, Language Proficiency
Timpe-Laughlin, Veronika; Sydorenko, Tetyana; Daurio, Phoebe – Computer Assisted Language Learning, 2022
Often, second/foreign (L2) language learners receive little opportunity to interact orally in the target language. Interactive, conversation-based spoken dialog systems (SDSs) that use automated speech recognition and natural language processing have the potential to address this need by engaging learners in meaningful, goal-oriented speaking…
Descriptors: Second Language Learning, Second Language Instruction, Oral Language, Dialogs (Language)
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)
Chen, Lei; Zechner, Klaus; Yoon, Su-Youn; Evanini, Keelan; Wang, Xinhao; Loukina, Anatassia; Tap, Jidong; Davis, Lawrence; Lee, Chong Min; Ma, Min; Mundowsky, Robert; Lu, Chi; Leong, Chee Wee; Gyawali, Binod – ETS Research Report Series, 2018
This research report provides an overview of the R&D efforts at Educational Testing Service related to its capability for automated scoring of nonnative spontaneous speech with the "SpeechRater"? automated scoring service since its initial version was deployed in 2006. While most aspects of this R&D work have been published in…
Descriptors: Computer Assisted Testing, Scoring, Test Scoring Machines, Speech Tests
Godwin-Jones, Robert – Language Learning & Technology, 2017
Although data collection has been used in language learning settings for some time, it is only in recent decades that large corpora have become available, along with efficient tools for their use. Advances in natural language processing (NLP) have enabled rich tagging and annotation of corpus data, essential for their effective use in language…
Descriptors: Computational Linguistics, Second Language Learning, Second Language Instruction, Phrase Structure
Grama, Ileana C.; Kerkhoff, Annemarie; Wijnen, Frank – Journal of Psycholinguistic Research, 2016
The ability to detect non-adjacent dependencies (i.e. between "a" and "b" in "aXb") in spoken input may support the acquisition of morpho-syntactic dependencies (e.g. "The princess 'is' kiss'ing' the frog"). Functional morphemes in morpho-syntactic dependencies are often marked by perceptual cues that render…
Descriptors: Role, Suprasegmentals, Intonation, Cues
Forbes-Riley, Kate; Litman, Diane – International Journal of Artificial Intelligence in Education, 2013
In this paper we investigate how student disengagement relates to two performance metrics in a spoken dialog computer tutoring corpus, both when disengagement is measured through manual annotation by a trained human judge, and also when disengagement is measured through automatic annotation by the system based on a machine learning model. First,…
Descriptors: Correlation, Learner Engagement, Oral Language, Computer Assisted Instruction
Wagner, Joachim; Foster, Jennifer; van Genabith, Josef – CALICO Journal, 2009
A classifier which is capable of distinguishing a syntactically well formed sentence from a syntactically ill formed one has the potential to be useful in an L2 language-learning context. In this article, we describe a classifier which classifies English sentences as either well formed or ill formed using information gleaned from three different…
Descriptors: Sentences, Language Processing, Natural Language Processing, Grammar
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