ONUBAD: A comprehensive dataset for automated conversion of Bangla regional dialects into standard Bengali dialectMendeley Data
Despite significant research on the Bangla language in Natural Language Processing (NLP), there remains a notable resource deficit for its diverse regional dialects, such as those spoken in Chittagong, Sylhet, and Barisal. These dialects, often considered unintelligible to speakers of Standard Benga...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925000083 |
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| Summary: | Despite significant research on the Bangla language in Natural Language Processing (NLP), there remains a notable resource deficit for its diverse regional dialects, such as those spoken in Chittagong, Sylhet, and Barisal. These dialects, often considered unintelligible to speakers of Standard Bengali, pose challenges due to their unique grammatical structures and phonetic variations. Some linguists categorize them as distinct languages. To address this, we present ONUBAD, a large and freely available dataset for the automatic translation of Chittagong, Sylhet, and Barisal dialects into Standard Bangla using a Neural Machine Translation (NMT) system. ONUBAD provides a parallel corpus of 1540 words, 130 clauses, and 980 sentences per regional dialect and their standard counterparts along with English translation. The dataset includes metadata on phonetic variations and grammatical features, aiming to bridge the gap between standard and non-standard forms of Bangla. It serves as a valuable resource for researchers in NLP, dialect studies, and linguistic preservation, helping to develop more accurate and contextually relevant translation models. The dataset was collected between July and September 2024 from diverse sources such as books, websites, and regional people with the help of regional dialect specialists. It is hosted by the Department of Computer Science and Engineering, Jahangirnagar University, and is freely accessible at https://data.mendeley.com/datasets/6ft99kf89b/2 |
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| ISSN: | 2352-3409 |