Resumo

LASKAR, Sahinur Rahman; MANNA, Riyanka; PAKRAY, Partha  e  BANDYOPADHYAY, Sivaji. A Domain Specific Parallel Corpus and Enhanced English-Assamese Neural Machine Translation. Comp. y Sist. [online]. 2022, vol.26, n.4, pp.1669-1687.  Epub 17-Mar-2023. ISSN 2007-9737.  https://doi.org/10.13053/cys-26-4-4423.

Machine translation deals with automatic translation from one natural language to another. Neural machine translation is a widely accepted technique of the corpus-based machine translation approach. However, an adequate amount of training data is required, and there is a need for the domain-wise parallel corpus to improve translational performance that shows translational coverages in various domains. In this work, a domain-specific parallel corpus is prepared that includes different domain coverages, namely, Agriculture, Government Office, Judiciary, Social Media, Tourism, COVID-19, Sports, and Literature domains for low-resource English-Assamese pair translation. Moreover, we have tackled data scarcity and word-order divergence problems via data augmentation and prior alignment concept. Also, we have contributed Assamese pretrained LM, Assamese word-embeddings by utilizing Assamese monolingual data, and a bilingual dictionary-based post-processing step to enhance transformer-based neural machine translation. We have achieved state-of-the-art results for both forward (English-to-Assamese) and backward (Assamese-to-English) directions of translation.

Palavras-chave : English-Assamese; low-resource; neural machine translation; parallel corpus; data augmentation; prior alignment; language model.

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