A Multilingual Reading Comprehension System for more than 100 Languages
Anthony Ferritto, Sara Rosenthal, Mihaela Bornea, Kazi Hasan, Rishav Chakravarti, Salim Roukos, Radu Florian, Avi Sil
Abstract
This paper presents M-GAAMA, a Multilingual Question Answering architecture and demo system. This is the first multilingual machine reading comprehension (MRC) demo which is able to answer questions in over 100 languages. M-GAAMA answers questions from a given passage in the same or different language. It incorporates several existing multilingual models that can be used interchangeably in the demo such as M-BERT and XLM-R. The M-GAAMA demo also improves language accessibility by incorporating the IBM Watson machine translation widget to provide additional capabilities to the user to see an answer in their desired language. We also show how M-GAAMA can be used in downstream tasks by incorporating it into an END-TO-END-QA system using CFO (Chakravarti et al., 2019). We experiment with our system architecture on the Multi-Lingual Question Answering (MLQA) and the COVID-19 CORD (Wang et al., 2020; Tang et al., 2020) datasets to provide insights into the performance of the system.
BibTeX
@inproceedings{ferritto-etal-2020-multilingual,
title = "A Multilingual Reading Comprehension System for more than 100 Languages",
author = "Ferritto, Anthony and
Rosenthal, Sara and
Bornea, Mihaela and
Hasan, Kazi and
Chakravarti, Rishav and
Roukos, Salim and
Florian, Radu and
Sil, Avi",
editor = "Ptaszynski, Michal and
Ziolko, Bartosz",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics: System Demonstrations",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics (ICCL)",
url = "https://aclanthology.org/2020.coling-demos.8/",
doi = "10.18653/v1/2020.coling-demos.8",
pages = "41--47"
}