arXiv subjects

Adity Khisa

Publications and source records attributed to Adity Khisa.

3 recordsLinked to original sources

arXiv2026

Re-educating Educated Ones: A Case Study on Chakma Language Revitalization in Chittagong Hill Tracts

Indigenous languages face significant cultural oppression from official state languages, particularly in the Global South. We investigate the Bangladeshi Chakma language revitalization movement, a community grappling with language liquidity and amalgamation into the dominant Bengali language. Our six-month-long qualitative study involving interviews and focus group discussions with Chakma language learning stakeholders uncovered existing community socio-economic challenges and resilience strategies. We noted the need for culturally grounded digital tools and resources. We propose an ICT-mediated community-centric framework for Indigenous language revitalization in the Global South, emphasizing the integration of historical identity elements, stakeholder-defined requirements, and effective digital engagement strategies to empower communities in preserving their linguistic and cultural heritage.

cs.HC↗

arXiv2025

Exploring Cross-Lingual Knowledge Transfer via Transliteration-Based MLM Fine-Tuning for Critically Low-resource Chakma Language

As an Indo-Aryan language with limited available data, Chakma remains largely underrepresented in language models. In this work, we introduce a novel corpus of contextually coherent Bangla-transliterated Chakma, curated from Chakma literature, and validated by native speakers. Using this dataset, we fine-tune six encoder-based transformer models, including multilingual (mBERT, XLM-RoBERTa, DistilBERT), regional (BanglaBERT, IndicBERT), and monolingual English (DeBERTaV3) variants on masked language modeling (MLM) tasks. Our experiments show that fine-tuned multilingual models outperform their pre-trained counterparts when adapted to Bangla-transliterated Chakma, achieving up to 73.54% token accuracy and a perplexity as low as 2.90. Our analysis further highlights the impact of data quality on model performance and shows the limitations of OCR pipelines for morphologically rich Indic scripts. Our research demonstrates that Bangla-transliterated Chakma can be very effective for transfer learning for Chakma language, and we release our dataset to encourage further research on multilingual language modeling for low-resource languages.

cs.CL↗

arXiv2025

Where Journalism Silenced Voices: Exploring Discrimination in the Representation of Indigenous Communities in Bangladesh

In this paper, we examine the intersections of indigeneity and media representation in shaping perceptions of indigenous communities in Bangladesh. Using a mixed-methods approach, we combine quantitative analysis of media data with qualitative insights from focus group discussions (FGD). First, we identify a total of 4,893 indigenous-related articles from our initial dataset of 2.2 million newspaper articles, using a combination of keyword-based filtering and LLM, achieving 77% accuracy and an F1-score of 81.9\%. From manually inspecting 3 prominent Bangla newspapers, we identify 15 genres that we use as our topics for semi-supervised topic modeling using CorEx. Results show indigenous news articles have higher representation of culture and entertainment (19%, 10% higher than general news articles), and a disproportionate focus on conflict and protest (9%, 7% higher than general news). On the other hand, sentiment analysis reveals that 57% of articles on indigenous topics carry a negative tone, compared to 27% for non-indigenous related news. Drawing from communication studies, we further analyze framing, priming, and agenda-setting (frequency of themes) to support the case for discrimination in representation of indigenous news coverage. For the qualitative part of our analysis, we facilitated FGD, where participants further validated these findings. Participants unanimously expressed their feeling of being under-represented, and that critical issues affecting their communities (such as education, healthcare, and land rights) are systematically marginalized in news media coverage. By highlighting 8 cases of discrimination and media misrepresentation that were frequently mentioned by participants in the FGD, this study emphasizes the urgent need for more equitable media practices that accurately reflect the experiences and struggles of marginalized communities.

cs.CY↗