Mining Bilingual Word Pairs from Comparable Corpus using Apache Spark Framework

Sanjanasri Jp, Vijay Krishna Menon, Soman Kp, Krzysztof Wolk


Abstract
Bilingual dictionaries are essential resources in many areas of natural language processing tasks, but resource-scarce and less popular language pairs rarely have such. Efficient automatic methods for inducting bilingual dictionaries are needed as manual resources and efforts are scarce for low-resourced languages. In this paper, we induce word translations using bilingual embedding. We use the Apache Spark framework for parallel computation. Further, to validate the quality of the generated bilingual dictionary, we use it in a phrase-table aided Neural Machine Translation (NMT) system. The system can perform moderately well with a manual bilingual dictionary; we change this into our inducted dictionary. The corresponding translated outputs are compared using the Bilingual Evaluation Understudy (BLEU) and Rank-based Intuitive Bilingual Evaluation Score (RIBES) metrics.
Anthology ID:
2021.bucc-1.2
Volume:
Proceedings of the 14th Workshop on Building and Using Comparable Corpora (BUCC 2021)
Month:
September
Year:
2021
Address:
Online (Virtual Mode)
Venue:
BUCC
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
2–7
Language:
URL:
https://aclanthology.org/2021.bucc-1.2
DOI:
Bibkey:
Cite (ACL):
Sanjanasri Jp, Vijay Krishna Menon, Soman Kp, and Krzysztof Wolk. 2021. Mining Bilingual Word Pairs from Comparable Corpus using Apache Spark Framework. In Proceedings of the 14th Workshop on Building and Using Comparable Corpora (BUCC 2021), pages 2–7, Online (Virtual Mode). INCOMA Ltd..
Cite (Informal):
Mining Bilingual Word Pairs from Comparable Corpus using Apache Spark Framework (Jp et al., BUCC 2021)
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PDF:
https://aclanthology.org/2021.bucc-1.2.pdf