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README.md

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+Vashantor: A Large-scale Multilingual Benchmark Dataset for Automated Translation of Bangla Regional Dialects to Bangla Language.
+
+Published: 15 January 2024
+Version 2
+DOI:
+10.17632/bj5jgk878b.2
+Contributors:
+Fatema Tuj Johora Faria
+Mukaffi Bin Moin
+Ahmed Al Wase
+Md. Rabius Sani
+Mehidi Ahmmed
+Tashreef Muhammad
+
+Description
+The Vashantor dataset consists of 32,500 sentences from different regions, including Chittagong, Noakhali, Sylhet, Barishal, and Mymensingh. It is categorized into two language formats: "Bangla" and "Banglish." Each region and language combination has specified quantities for training, testing, and validation samples. The dataset details are as follows:
+
+Specifics of the Core Data:
+—-------------------------------
+Bangla: Train 1875, Test 375, Validation 250 (Total 2500)
+Banglish: Train 1875, Test 375, Validation 250 (Total 2500)
+English: Train 1875, Test 375, Validation 250 (Total 2500)
+
+
+Specifics of the Regional Data:
+—--------------------------------------
+Chittagong:
+—------------
+Bangla: Train 1875, Test 375, Validation 250 (Total 2500)
+Banglish: Train 1875, Test 375, Validation 250 (Total 2500)
+
+Noakhali:
+—---------
+Bangla: Train 1875, Test 375, Validation 250 (Total 2500)
+Banglish: Train 1875, Test 375, Validation 250 (Total 2500)
+
+Sylhet:
+—------
+Bangla: Train 1875, Test 375, Validation 250 (Total 2500)
+Banglish: Train 1875, Test 375, Validation 250 (Total 2500)
+
+Barishal:
+—---------
+Bangla: Train 1875, Test 375, Validation 250 (Total 2500)
+Banglish: Train 1875, Test 375, Validation 250 (Total 2500)
+
+Mymensingh:
+—---------------
+Bangla: Train 1875, Test 375, Validation 250 (Total 2500)
+Banglish: Train 1875, Test 375, Validation 250 (Total 2500)
+
+Cite this : 
+
+Faria, Fatema Tuj Johora ; Bin Moin, Mukaffi; Al Wase, Ahmed; Sani, Md. Rabius; Ahmmed, Mehidi; Muhammad, Tashreef (2024), “Vashantor: A Large-scale Multilingual Benchmark Dataset for Automated Translation of Bangla Regional Dialects to Bangla Language”, Mendeley Data, V2, doi: 10.17632/bj5jgk878b.2