Séminaires RALI-OLST

A BERT-Based Approach for Multilingual Discourse Connective Detection

Thomas Chapados Muermans (thomas (point) chapadosmuermans <at> mail (point) concordia (point) ca)

Computer Science & Software Engineering, Concordia University

Le mercredi 18 mai 2022 à 11 h 30

Réunion Zoom, ci-dessous

In this paper, we report on our experiments towards multilingual discourse connective (or DC) identification and show how language specific BERT models seem to be sufficient even with little task-specific training data. While some languages have large corpora with human annotated DCs, most languages are low in such resources. Hence, relying solely on discourse annotated corpora to train a DC identification system for low resourced languages is insufficient. To address this issue, we developed a model based on pretrained BERT and fine-tuned it with discourse annotated data of varying sizes. To measure the effect of larger training data, we induced synthetic training corpora with DC annotations using word-aligned parallel corpora. We evaluated our models on 3 languages: English, Turkish and Mandarin Chinese in the context of the recent DISRPT 2021 Task 2 shared task. Results show that the F-measure achieved by the standard BERT model (2.49%, 93.97%, 87.42% for English, Turkish and Chinese) is hard to improve upon even with larger task specific training corpora.

Recording : https://drive.google.com/file/d/1Uh0SJ6Z6qOq3qdksg54qcCAjYnGs4It6/view?usp=sharing

Joignez-vous à nous avec Zoom à l'aide de cette URL.
ID de réunion : 916 9097 5818, Code : 343273.
Numéros de téléphone : https://umontreal.zoom.us/u/abitNZzLg.
One tap mobile : +14388097799,,91690975818#,,,,,,0#,,343273#

Suivez ce lien pour vous inscrire à la liste de diffusion RALI-OLST.

Liste de tous les séminaires pour l'année :

1991 1992 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024