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Showing all 14 results Save | Export
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Daniel Swingley; Robin Algayres – Cognitive Science, 2024
Computational models of infant word-finding typically operate over transcriptions of infant-directed speech corpora. It is now possible to test models of word segmentation on speech materials, rather than transcriptions of speech. We propose that such modeling efforts be conducted over the speech of the experimental stimuli used in studies…
Descriptors: Sentences, Word Recognition, Psycholinguistics, Infants
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Samar Ibrahim; Ghazala Bilquise – Education and Information Technologies, 2025
Language is an essential component of human communication and interaction. Advances in Artificial Intelligence (AI) technology, specifically in Natural Language Processing (NLP) and speech-recognition, have made is possible for conversational agents, also known as chatbots, to converse with language learners in a way that mimics human speech.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Benchmarking
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Galit Agmon; Sameer Pradhan; Sharon Ash; Naomi Nevler; Mark Liberman; Murray Grossman; Sunghye Cho – Journal of Speech, Language, and Hearing Research, 2024
Purpose: Multiple methods have been suggested for quantifying syntactic complexity in speech. We compared eight automated syntactic complexity metrics to determine which best captured verified syntactic differences between old and young adults. Method: We used natural speech samples produced in a picture description task by younger (n = 76, ages…
Descriptors: Young Adults, Older Adults, Undergraduate Students, Caregivers
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Jiang, Hang; Frank, Michael C.; Kulkarni, Vivek; Fourtassi, Abdellah – Cognitive Science, 2022
The linguistic input children receive across early childhood plays a crucial role in shaping their knowledge about the world. To study this input, researchers have begun applying distributional semantic models to large corpora of child-directed speech, extracting various patterns of word use/co-occurrence. Previous work using these models has not…
Descriptors: Caregivers, Caregiver Child Relationship, Linguistic Input, Semantics
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Tzu-Yu Tai; Howard Hao-Jan Chen – Computer Assisted Language Learning, 2024
English speaking is considered the most difficult and anxiety-provoking language skill for EFL learners due to lack of access to authentic language use, fear of making mistakes, and peers' negative comments. With automatic speech recognition and natural language processing, intelligent personal assistants (IPAs) have potential in foreign language…
Descriptors: English (Second Language), Speech Communication, English Language Learners, Anxiety
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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)
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Sinclair, Jeanne; Jang, Eunice Eunhee; Rudzicz, Frank – Journal of Educational Psychology, 2021
Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…
Descriptors: Prediction, Reading Comprehension, Natural Language Processing, Speech Communication
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Huang, Xinyi; Zou, Di; Cheng, Gary; Chen, Xieling; Xie, Haoran – Educational Technology & Society, 2023
Artificial Intelligence (AI) plays an increasingly important role in language education; however, the trends, research issues, and applications of AI in language learning remain largely under-investigated. Accordingly, the present paper, using bibliometric analysis, investigates these issues via a review of 516 papers published between 2000 and…
Descriptors: Trend Analysis, Educational Trends, Vocabulary Development, Artificial Intelligence
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Abbas, Ali; Sarfraz, Summaira – Journal of Educational Technology Systems, 2018
The purpose of the study is to provide a literature review of the work done on sign language (SL) around the world and in Pakistan and to develop a translation tool of speech and text to Pakistan Sign Language (PSL) with bilingual subtitles. Information and communication technology and tools development for teaching and learning purposes improve…
Descriptors: Bilingualism, Sign Language, Computer Software, Programming
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Minichino, Mario; Berson, Michael J. – SRATE Journal, 2012
This article is an exploration of the available applications for speech to speech real-time translation software for use in the classroom. Three different types of machine language translation (MLT) software and devices are reviewed for their features and practical application in secondary education classrooms.
Descriptors: Translation, Computer Software, Courseware, Computational Linguistics
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Johnson, Elizabeth K.; Tyler, Michael D. – Developmental Science, 2010
Past research has demonstrated that infants can rapidly extract syllable distribution information from an artificial language and use this knowledge to infer likely word boundaries in speech. However, artificial languages are extremely simplified with respect to natural language. In this study, we ask whether infants' ability to track transitional…
Descriptors: Cues, Artificial Languages, Testing, Infants
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Swerts, Marc; van Wijk, Carel – Discourse Processes: A Multidisciplinary Journal, 2010
Tennis scores represent a natural language domain that offers the unique opportunity to study the effects of discourse constraints on prosody with strict control over syntactic and lexical variation. This study analyzed a set of tennis scores, such as "30-15," from live recordings of several Wimbledon and Davis Cup matches. The objective was to…
Descriptors: Racquet Sports, Natural Language Processing, Scores, Language Usage
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Morris, Bradley J. – Journal of Cognition and Development, 2008
Why is it that young children use connectives correctly in conversation, yet frequently err when asked to use the same connectives in formal reasoning? One possibility is that connective acquisition is item-based in which usage rules are induced from natural language input. This possibility was evaluated by examining the correspondence between the…
Descriptors: Language Patterns, Linguistic Input, Natural Language Processing, Speech Communication
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Stewart, Iain A. D.; File, Portia – Computer Assisted Language Learning, 2007
Early and intermediate second language (L2) learners often encounter difficulties when engaging in introductory social conversations, typically having had little opportunity to practise such interactions. This article describes a project to design and prototype a computer dialogue system, Let's Chat, which would allow learners to rehearse social…
Descriptors: Second Language Learning, Speech Communication, Linguistic Input, Language Processing