SAHAAYAK 2023 -- the Multi Domain Bilingual Parallel Corpus of Sanskrit to Hindi for Machine Translation
This provides a valuable dataset for machine translation research in low-resource languages, though it is incremental as it focuses on data collection rather than novel methods.
The authors tackled the lack of bilingual data for the low-resource Sanskrit-Hindi language pair by creating SAHAAYAK 2023, a multi-domain parallel corpus containing 1.5 million sentence pairs from sources like news and ancient literature.
The data article presents the large bilingual parallel corpus of low-resourced language pair Sanskrit-Hindi, named SAHAAYAK 2023. The corpus contains total of 1.5M sentence pairs between Sanskrit and Hindi. To make the universal usability of the corpus and to make it balanced, data from multiple domain has been incorporated into the corpus that includes, News, Daily conversations, Politics, History, Sport, and Ancient Indian Literature. The multifaceted approach has been adapted to make a sizable multi-domain corpus of low-resourced languages like Sanskrit. Our development approach is spanned from creating a small hand-crafted dataset to applying a wide range of mining, cleaning, and verification. We have used the three-fold process of mining: mining from machine-readable sources, mining from non-machine readable sources, and collation from existing corpora sources. Post mining, the dedicated pipeline for normalization, alignment, and corpus cleaning is developed and applied to the corpus to make it ready to use on machine translation algorithms.