Research Publications Presentations Texts and Tools Lab Courses


The main thrust of my research is to applying educational technology to language learning, specifically I am interested in how rule-based and probablistic pattern matching can be harnessed to help language learners and language users better understand scientific discourse. My research is multidisciplinary covering applied linguistics, computer-assisted language learning, education and touching on computer science and statistics. I draw heavily on corpus and computational linguistics.

Research themes

  • Pronunciation Scaffolder This version annotates presentation scripts to help users read their script aloud. Features annotated include pausing, intonation, content words, word stress, tricky sounds and linking between words. The initial prototypes were created by computer science majors in EL317 language and patterns class of 2017.
  • Error detector This tool detects errors found in a corpus of information and computer science short research articles. Automated feedback is given for accuracy, brevity, clarity, objectivity and formality errors.
  • Language feature detector This tool detects various language features, including: modality (hedges, approximations and boosters), voice, pronouns and articles.
  • Language feature visualizer. This tool visualizes language features in a pre-loaded pre-annotated corpus of short research articles and academic essays (beta release expected soon).
  • Gist Visualizer. This tool highlights the main gist in texts using simplified SVOCA analysis using an NLP pipeline coded in Python (subject to funding) to identify the finite verbs and their grammatical subjects.

Competitive funding

Successful researchers need ability, grit, a dash of luck and a plentiful supply of funds. I have grit and have recently been rather successful at drawing down funding. Ability and luck, however, are still in short supply.

    JSPS Kakenhi Grant-in-aid

    UoA Competitive Research Fund

  • FY2019 Principal Investigator - Tense Activator: Automatic identification and explanation of tense in context
  • FY2019 Co-Investigator - Speech prosody modeling, visualization and estimation in an interdisciplinary discourse
  • FY2019 Co-Investigator - Professional communicative writing and pragmatics: Addressing the needs of University of Aizu students
  • FY2018 Principal Investigator - Interactive language feature visualizer for thesis writing
  • FY2017 Principal Investigator - Online error detection and feedback tool for graduate theses
  • FY2017 Co-Investigator - Graduation thesis and presentation development through student-produced video

    UoA Strategic Research Fund

  • FY2017 Co-Investigator - Project-based language learning: A model for Fukushima revitalization