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The Bangla linguistic variety is a fascinating mix of regional dialects thatadds to the cultural diversity of the Bangla-speaking community. Despiteextensive study into translating Bangla to English, English to Bangla, andBanglish to Bangla in the past, there has been a noticeable gap in translatingBangla regional dialects into standard Bangla. In this study, we set out tofill this gap by creating a collection of 32,500 sentences, encompassingBangla, Banglish, and English, representing five regional Bangla dialects. Ouraim is to translate these regional dialects into standard Bangla and detectregions accurately. To achieve this, we proposed models known as mT5 andBanglaT5 for translating regional dialects into standard Bangla. Additionally,we employed mBERT and Bangla-bert-base to determine the specific regions fromwhere these dialects originated. Our experimental results showed the highestBLEU score of 69.06 for Mymensingh regional dialects and the lowest BLEU scoreof 36.75 for Chittagong regional dialects. We also observed the lowest averageword error rate of 0.1548 for Mymensingh regional dialects and the highest of0.3385 for Chittagong regional dialects. For region detection, we achieved anaccuracy of 85.86% for Bangla-bert-base and 84.36% for mBERT. This is the firstlarge-scale investigation of Bangla regional dialects to Bangla machinetranslation. We believe our findings will not only pave the way for future workon Bangla regional dialects to Bangla machine translation, but will also beuseful in solving similar language-related challenges in low-resource languageconditions.

Vashantor: A Large-scale Multilingual Benchmark Dataset for Automated Translation of Bangla Regional Dialects to Bangla Language