@inproceedings{pawar-etal-2023-evaluating,
title = "Evaluating Cross Lingual Transfer for Morphological Analysis: a Case Study of {I}ndian Languages",
author = "Pawar, Siddhesh and
Bhattacharyya, Pushpak and
Talukdar, Partha",
editor = {Nicolai, Garrett and
Chodroff, Eleanor and
Mailhot, Frederic and
{\c{C}}{\"o}ltekin, {\c{C}}a{\u{g}}r{\i}},
booktitle = "Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/remove-affiliations/2023.sigmorphon-1.3/",
doi = "10.18653/v1/2023.sigmorphon-1.3",
pages = "14--26",
abstract = "Recent advances in pretrained multilingual models such as Multilingual T5 (mT5) have facilitated cross-lingual transfer by learning shared representations across languages. Leveraging pretrained multilingual models for scaling morphology analyzers to low-resource languages is a unique opportunity that has been under-explored so far. We investigate this line of research in the context of Indian languages, focusing on two important morphological sub-tasks: root word extraction and tagging morphosyntactic descriptions (MSD), viz., gender, number, and person (GNP). We experiment with six Indian languages from two language families (Dravidian and Indo-Aryan) to train a multilingual morphology analyzers for the first time for Indian languages. We demonstrate the usability of multilingual models for few-shot cross-lingual transfer through an average 7{\%} increase in GNP tagging in a cross-lingual setting as compared to a monolingual setting through controlled experiments. We provide an overview of the state of the datasets available related to our tasks and point-out a few modeling limitations due to datasets. Lastly, we analyze the cross-lingual transfer of morphological tags for verbs and nouns, which provides a proxy for the quality of representations of word markings learned by the model."
}
Markdown (Informal)
[Evaluating Cross Lingual Transfer for Morphological Analysis: a Case Study of Indian Languages](https://preview.aclanthology.org/remove-affiliations/2023.sigmorphon-1.3/) (Pawar et al., SIGMORPHON 2023)
ACL