The geopolitical division between the indigenous Chakma population and mainstream Bangladesh creates a significant cultural and linguistic gap, as the Chakma community, mostly residing in the hill tracts of Bangladesh, maintains distinct cultural traditions and language. Developing a Machine Translation (MT) model or Chakma to Bangla could play a crucial role in alleviating this cultural-linguistic divide. Thus, we have worked on MT between CCP-BN(Chakma-Bangla) by introducing a novel dataset of 15,021 parallel samples and 42,783 monolingual samples of the Chakma Language. Moreover, we introduce a small set for Benchmarking containing 600 parallel samples between Chakma, Bangla, and English. We ran traditional and state-of-the-art models in NLP on the training set, where fine-tuning BanglaT5 with back-translation using transliteration of Chakma achieved the highest BLEU score of 17.8 and 4.41 in CCP-BN and BN-CCP respectively on the Benchmark Dataset. As far as we know, this is the first-ever work on MT for the Chakma Language. Hopefully, this research will help to bridge the gap in linguistic resources and contribute to preserving endangered languages. Our dataset link and codes will be published soon.

本研究针对查克马语和孟加拉语之间的文化语言差距，开发了一种机器翻译模型。通过引入包含15,021个平行样本和42,783个单语样本的新数据集，我们的研究首次实现了查克马语言的机器翻译，并在基准测试中取得了最佳BLEU分数。这项工作有望弥补语言资源的不足，促进濒危语言的保护。

ChakmaNMT：低资源的查克马语言机器翻译