ARPA: Armenian Paraphrase Detection Corpus and Models
Computation and Language
2020-09-29 v1
Abstract
In this work, we employ a semi-automatic method based on back translation to generate a sentential paraphrase corpus for the Armenian language. The initial collection of sentences is translated from Armenian to English and back twice, resulting in pairs of lexically distant but semantically similar sentences. The generated paraphrases are then manually reviewed and annotated. Using the method train and test datasets are created, containing 2360 paraphrases in total. In addition, the datasets are used to train and evaluate BERTbased models for detecting paraphrase in Armenian, achieving results comparable to the state-of-the-art of other languages.
Keywords
Cite
@article{arxiv.2009.12615,
title = {ARPA: Armenian Paraphrase Detection Corpus and Models},
author = {Arthur Malajyan and Karen Avetisyan and Tsolak Ghukasyan},
journal= {arXiv preprint arXiv:2009.12615},
year = {2020}
}
Comments
To be published in the proceedings of Ivannikov Memorial Workshop 2020