@article {10.3844/jcssp.2021.924.952,
article_type = {journal},
title = {A Systematic Literature Review on Extraction of Parallel Corpora from Comparable Corpora},
author = {Kaur, Dilshad and Singh, Satwinder},
volume = {17},
number = {10},
year = {2021},
month = {Oct},
pages = {924-952},
doi = {10.3844/jcssp.2021.924.952},
url = {https://thescipub.com/abstract/jcssp.2021.924.952},
abstract = {In today’s Globalized Scenario, the requirement for translation is high and increasing rapidly in the number of fields, but it is difficult to translate everything manually. Machine Translation, which is dependent on corpora availability, is a medium for meeting this high demand for translation. Parallel corpora are used to gain most translation knowledge. But, the number and quality of parallel corpora are critical. Because parallel corpora are not readily accessible for many different language pairs, comparable corpora that are widely accessible can be used to extract parallel corpora. A systematic literature survey is performed on 188 research articles that are published in premier journals, conferences, workshops and book chapters. The research process is carried out while considering the research questions. Different MT systems along with their features are identified. Several datasets and techniques for bilingual lexicon extraction, parallel sentence and fragment extraction are revealed. A proposed architecture and a mind map are also showcased in this review article to provide better clarity regarding parallel data extraction using comparable corpora. The study of the paper will increase readers' understanding of parallel data mining through bilingual lexicons, parallel sentences and fragments.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}