Myanmar Women In Tech: Research and Analysis
Interactive data visualization dashboard analyzing workforce demographics, challenges, and career experiences of women in Myanmar's tech sector.
Research & Development
Browse our published research papers, open-source software tools, and focus areas.
All Publications & Products
Browse our published products, datasets, and academic publications.
Women and Technology
Explore Focus Area →Low Resource Languages
Explore Focus Area →mmdt-tokenizer
"mmdt-tokenizer" is an open-source Python toolkit for Myanmar-language text segmentation. It uses a transparent, grammar-informed pipeline to protect URLs, emails, dates, phone numbers, and numeric expressions before segmenting text into syllable- and word-level units. Curated linguistic lexicons and structural rules recognize postpositions, conjunctions, classifiers, verbal particles, and sentence-final particles, while merging related predicate constructions into meaningful tokens. Designed for low-resource settings, the system is lightweight, auditable, and extensible without model retraining, providing essential language infrastructure for Myanmar NLP research, corpus development, search, information extraction, and other language technologies.
MMDT NER
MMDT NER is a foundational language technology project that transforms unstructured Burmese text into structured, usable data by identifying people, organizations, locations, dates, times, and numerical expressions. Built on a 2.14-million-token annotated corpus, it combines transformer-based modeling and responsible evaluation to advance context-aware AI for Burmese—an underrepresented, low-resource language—and support research, journalism, digital archives, humanitarian initiatives, and other public-interest applications.