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TransPhoner: automated mnemonic keyword generation

Published: 26 April 2014 Publication History

Abstract

We present TransPhoner: a system that generates keywords for a variety of scenarios including vocabulary learning, phonetic transliteration, and creative word plays. We select effective keywords by considering phonetic, orthographic and semantic word similarity, and word concept imageability. We show that keywords provided by TransPhoner improve learner performance in an online vocabulary learning study, with the improvement being more pronounced for harder words. Participants rated TransPhoner keywords as more helpful than a random keyword baseline, and almost as helpful as manually selected keywords. Comments also indicated higher engagement in the learning task, and more desire to continue learning. We demonstrate additional applications to tasks such as pure phonetic transliteration, generation of mnemonics for complex vocabulary, and topic-based transformation of song lyrics.

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TransPhoner

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  • (2023)SmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual CuesArtificial Intelligence in Education10.1007/978-3-031-36272-9_2(16-27)Online publication date: 26-Jun-2023
  • (2020)Enhancing Memory For Technical Lists With Computer-Generated Mnemonics2020 Sixth International Conference on e-Learning (econf)10.1109/econf51404.2020.9385452(271-274)Online publication date: 6-Dec-2020
  • (2020)Towards Computer-Generated Cue-Target Mnemonics for E-LearningComputational Science and Technology10.1007/978-981-15-0058-9_37(383-392)Online publication date: 2020
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    cover image ACM Conferences
    CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
    April 2014
    4206 pages
    ISBN:9781450324731
    DOI:10.1145/2556288
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 26 April 2014

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    1. mnemonic keywords

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    CHI '14: CHI Conference on Human Factors in Computing Systems
    April 26 - May 1, 2014
    Ontario, Toronto, Canada

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    CHI '14 Paper Acceptance Rate 465 of 2,043 submissions, 23%;
    Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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    View all
    • (2023)SmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual CuesArtificial Intelligence in Education10.1007/978-3-031-36272-9_2(16-27)Online publication date: 26-Jun-2023
    • (2020)Enhancing Memory For Technical Lists With Computer-Generated Mnemonics2020 Sixth International Conference on e-Learning (econf)10.1109/econf51404.2020.9385452(271-274)Online publication date: 6-Dec-2020
    • (2020)Towards Computer-Generated Cue-Target Mnemonics for E-LearningComputational Science and Technology10.1007/978-981-15-0058-9_37(383-392)Online publication date: 2020
    • (2017)ViVoProceedings of the 2017 CHI Conference on Human Factors in Computing Systems10.1145/3025453.3025779(5568-5579)Online publication date: 2-May-2017
    • (2017)Learning and immediate retention of Japanese vocabulary using generated mnemonic keywords2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)10.1109/SNPD.2017.8022739(315-320)Online publication date: Jun-2017
    • (2015)Automated English mnemonic keyword suggestion for learning Japanese vocabulary2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)10.1109/ICITEED.2015.7409024(638-643)Online publication date: Oct-2015

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