no code implementations • 19 Feb 2024 • Tatsuki Kuribayashi, Ryo Ueda, Ryo Yoshida, Yohei Oseki, Ted Briscoe, Timothy Baldwin
This also showcases the advantage of cognitively-motivated LMs, which are typically employed in cognitive modeling, in the computational simulation of language universals.
no code implementations • 9 Nov 2022 • Christopher Bryant, Zheng Yuan, Muhammad Reza Qorib, Hannan Cao, Hwee Tou Ng, Ted Briscoe
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text.
1 code implementation • EMNLP (CODI) 2020 • Youmna Farag, Josef Valvoda, Helen Yannakoudakis, Ted Briscoe
In this work, we systematically investigate how well current models of coherence can capture aspects of text implicated in discourse organisation.
no code implementations • WS 2019 • Christopher Bryant, Mariano Felice, {\O}istein E. Andersen, Ted Briscoe
This paper reports on the BEA-2019 Shared Task on Grammatical Error Correction (GEC).
1 code implementation • WS 2016 • Menglin Xia, Ekaterina Kochmar, Ted Briscoe
This paper addresses the task of readability assessment for the texts aimed at second language (L2) learners.
no code implementations • NAACL 2019 • Menglin Xia, Ekaterina Kochmar, Ted Briscoe
Automating the assessment of learner summaries provides a useful tool for assessing learner reading comprehension.
no code implementations • WS 2018 • Meng Zhang, Xie Chen, Ronan Cummins, {\O}istein E. Andersen, Ted Briscoe
Some language exams have multiple writing tasks.
no code implementations • WS 2018 • Christopher Bryant, Ted Briscoe
Since the end of the CoNLL-2014 shared task on grammatical error correction (GEC), research into language model (LM) based approaches to GEC has largely stagnated.
1 code implementation • NAACL 2018 • Youmna Farag, Helen Yannakoudakis, Ted Briscoe
We demonstrate that current state-of-the-art approaches to Automated Essay Scoring (AES) are not well-suited to capturing adversarially crafted input of grammatical but incoherent sequences of sentences.
no code implementations • 29 Nov 2017 • Ahmed H. Zaidi, Russell Moore, Ted Briscoe
The structure of curriculum plays a vital role in our learning process, both as children and adults.
no code implementations • WS 2017 • Youmna Farag, Marek Rei, Ted Briscoe
Additionally, extending the model with corrections provides further performance gains when data sparsity is an issue.
no code implementations • WS 2017 • Marek Rei, Mariano Felice, Zheng Yuan, Ted Briscoe
Shortage of available training data is holding back progress in the area of automated error detection.
Ranked #3 on Grammatical Error Detection on FCE
1 code implementation • ACL 2017 • Christopher Bryant, Mariano Felice, Ted Briscoe
Until now, error type performance for Grammatical Error Correction (GEC) systems could only be measured in terms of recall because system output is not annotated.
no code implementations • COLING 2016 • Mariano Felice, Christopher Bryant, Ted Briscoe
We propose a new method of automatically extracting learner errors from parallel English as a Second Language (ESL) sentences in an effort to regularise annotation formats and reduce inconsistencies.