Journal Article2025Cited by 9

ChatgaiyyaAlap: A dataset for conversion from Chittagonian dialect to standard Bangla

Sinthia Chowdhury, Deawan Rakin Ahamed Remal, Syed Tangim Pasha, Ashraful Islam, Sheak Rashed Haider Noori

Data in Brief

Elsevier BV, Vol. 59, pp. 111413, ISBN: 2352-3409

DOI: 10.1016/j.dib.2025.111413Open AccessURL

Abstract

Bangla is one of the most used languages around the world with 240 million speakers. The standard Bangla language is the official language of people from Bangladesh and a few other parts outside Bangladesh, like West Bengal and Tripura. Although, people from different areas of Bangladesh do not use standard Bangla on a day-to-day basis. Instead, dialects of the Bangla language are used. The dialects of the Bangla language are quite diverse which includes the Rajshahi dialect, Sylheti dialect, Old Dhaka dialect, Chittagonian dialect, and many more. Nearly every division of Bangladesh has its unique dialect which adds linguistic diversity to the language. The main difference between the standard Bangla language and Chittagonian dialect is that it does not have any written form and the words vary from the standard Bangla. We built a dataset containing standard Bangla and one of its most used dialects: the Chittagonian dialect. Our dataset, “ChatgaiyyaAlap,” was created by combining 4012 unique sentences in standard Bangla with their Chittagonian translations, which were gathered from dramas, comments, and videos on YouTube and Facebook. In our dataset, we cleaned the data by removing emojis, punctuations, and unessential spaces. The dissimilarity in spelling as well as in sentence structure between standard Bangla and Chittagonian dialects, particularly in negative sentences can be clearly visible through this dataset. Additionally, to maintain the data accuracy, we developed a dictionary containing 1,500 standard Bangla words and their Chittagonian form. The dictionary showcases significant variation in the vocabulary of both languages and resolves ambiguities along with potential biases. To perform a word-to-word translation this dictionary would be useful, while for studying comparative linguistics and developing intelligent systems the ChatgaiyyaAlap dataset might assist the researchers. Moreover, this dataset can be utilized to train language models for linguistic translation.

Keywords

  • comparative linguistics
  • spelling variation
  • negative sentences
  • low-resource translation
  • dialect dictionary

CCDS Authors

Deawan Rakin Ahamed Remal
Deawan Rakin Ahamed Remal

Deawan Rakin Ahamed Remal

  • Research Assistant, HCI Wing

Published at

HCII

Research Interests

Natural Language Processing, Health Informatics, Human-Computer Interaction, Computer Vision

Syed Tangim Pasha
Syed Tangim Pasha

Syed Tangim Pasha

  • Collaborator, HCI Wing

Lecturer

Department of Computing and Information System

Daffodil International University

Published at

UbiComp

Research Interests

Health Informatics, Affective Computing, Digital Health, Wearable Computing

Ashraful Islam, PhD
Ashraful Islam

Ashraful Islam, PhD

  • Center Director, CCDS
  • Director, HCI Wing

Assistant Professor

Department of Computer Science and Engineering

Independent University, Bangladesh (IUB)

Published at

CHI, UIST, UbiComp, IJCNN, ICIP, HCII, ICDMW, BLP, IEEE Internet of Things Journal, JMIR, JMIR Human Factors, JMIR Formative Research, IEEE Access, Smart Agricultural Technology, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Human-Computer Interaction, AI for Social Good, AI for Public Health, AI for Impact

References

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  3. 3.Sinthia Chowdhury, Deawan Rakin Ahamed Remal, Syed Tangim Pasha, Ashraful Islam, Sheak Rashed Haider Noori. (2025). ChatgaiyyaAlap: A dataset for conversion from Chittagonian dialect to standard Bangla. Data in Brief, 59, 111413[10.1016/j.dib.2025.111413]
  4. 4.Hafizur Rahman Milon, Sheikh Nasir Uddin Sabbir, Azfar Inan, Nahid Hossain. (2020). A Comprehensive Dialect Conversion Approach from Chittagonian to Standard Bangla. 2020 IEEE Region 10 Symposium (TENSYMP), 214–217[10.1109/tensymp50017.2020.9230714]

Cited By

  1. 1.Nusrat Sultana, Rumana Yasmin, Bijon Mallik, Mohammad Shorif Uddin. (2025). ONUBAD: A comprehensive dataset for automated conversion of Bangla regional dialects into standard Bengali dialect. Data in Brief, 58, 111276[10.1016/j.dib.2025.111276]
  2. 2.Sinthia Chowdhury, Deawan Rakin Ahamed Remal, Syed Tangim Pasha, Ashraful Islam, Sheak Rashed Haider Noori. (2025). ChatgaiyyaAlap: A dataset for conversion from Chittagonian dialect to standard Bangla. Data in Brief, 59, 111413[10.1016/j.dib.2025.111413]
  3. 3.Prataoy Kabya Bhowmik, Khadija Akter Sonia, Katharine Selby, Proloy Barua, Justine Howard. (2026). Understanding the factors associated with youths’ NEET status in humanitarian settings in Bangladesh. International Journal of Educational Development, 124, 103604[10.1016/j.ijedudev.2026.103604]
  4. 4.Md. Atique Faisal, Farhan Sadaf, Dipta Chowdhury, H.M. Azrof, Monojit Paul Tanmay. (2026). Kothon: A large-scale dataset for machine translation of the Chittagonian and Sylheti dialects into standard Bangla. Data in Brief, 66, 112789[10.1016/j.dib.2026.112789]
  5. 5.Md Monir Ahammod Bin Atique, Md. Morshed Ali, Kashfi Shormita Kushal, Nezam Uddin, Mehedi Hasan Saurav, Md Sharifuzzaman Shajib. (2026). BPS2025: A demographically focused dataset of handwritten bangla primary script for early writer recognition. Data in Brief, 66, 112700[10.1016/j.dib.2026.112700]
  6. 6.Anika Rahman, Nafesha Hasan Muna, Masuma Saba Prity. (2026). Dataset on multiregional variations of Bangla language (BD-Dialect). Data in Brief, 66, 112654[10.1016/j.dib.2026.112654]
  7. 7.Sinthia Chowdhury, Deawan Rakin Ahamed Remal, Sefatul Wasi, Ashraful Islam, Moinul Zaber, M. Ashraful Amin. (2026). Designing Conversational User Interface with Low-Resource Bi-directional Machine Translation for Chittagonian Dialect to Regular Bangla Health Dialogues. Communications in computer and information science, 193–203[10.1007/978-3-032-30833-7_21]
  8. 8.Tasmia Nawrin, Md Munnaf Hosen Munna. (2026). Learning Needs for Standard Bangla among Tertiary-Level Native Speakers: A Qualitative Study of Dialect-to-Standard Transition in Bangladesh. Open Journal of Modern Linguistics, 16(04), 375–393[10.4236/ojml.2026.164025]
  9. 9.Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Ashraful Islam, S. M. Rakibul Islam, Nabarun Halder, Faiza Omar Arpita, Jahanggir Hossain Setu, Asif Mahmud, M. Ashraful Amin. (2025). Effectiveness of Transfer Learning Approach for Low-Resource Bangla Dialect Translation. IEEE Student Conference on Research and Development (SCOReD), 1–6[10.1109/scored68498.2025.11399036]
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