no code implementations • RANLP 2021 • John Lee, Chak Yan Yeung
When the user makes at least half of the expected updates to the open learner model, simulation results show that it outperforms the graded approach in retrieving texts that fit user preference for new-word density.
no code implementations • EACL (BEA) 2021 • Chak Yan Yeung, John Lee
To promote efficient learning of Chinese characters, pedagogical materials may present not only a single character, but a set of characters that are related in meaning and in written form.
no code implementations • LREC 2020 • Ildiko Pilan, John Lee, Chak Yan Yeung, Jonathan Webster
The dataset consists of student-written sentences in their original and revised versions with teacher feedback provided for the errors.
no code implementations • WS 2019 • John Lee, Chak Yan Yeung
In the typical LS pipeline, the Substitution Ranking step determines the best substitution out of a set of candidates.
no code implementations • COLING 2018 • Chak Yan Yeung, John Lee
This paper describes a personalized text retrieval algorithm that helps language learners select the most suitable reading material in terms of vocabulary complexity.
no code implementations • COLING 2018 • John Lee, Chak Yan Yeung
A lexical simplification (LS) system aims to substitute complex words with simple words in a text, while preserving its meaning and grammaticality.
no code implementations • IJCNLP 2017 • Chak Yan Yeung, John Lee
We present the first study that evaluates both speaker and listener identification for direct speech in literary texts.
no code implementations • LREC 2016 • John Lee, Chak Yan Yeung
We propose a scheme for annotating direct speech in literary texts, based on the Text Encoding Initiative (TEI) and the coreference annotation guidelines from the Message Understanding Conference (MUC).