@inproceedings{bharati-etal-2026-ajamimorph,
    title = "{A}jami{M}orph: Zero-Annotation Morphological Discovery for {H}ausa Ajami via Multi-Method Consensus",
    author = "Bharati, Soumedhik  and
      Mandal, Shibam  and
      Ghosh, Prithwish  and
      Ghosh, Swarup Kr  and
      Mondal, Sayani",
    booktitle = "Proceedings of the 2nd Workshop on {NLP} for Languages Using {A}rabic Script",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/manual-author-scripts/2026.abjadnlp-1.23/",
    pages = "166--171",
    abstract = "Hausa Ajami (Hausa written in Arabic script) remains severely under-resourced for computational morphology. We present AjamiMorph, a zero-annotation framework that discovers morphemes through consensus among three unsupervised methods, namely, Byte Pair Encoding (BPE), transition-based boundary detection using Pointwise Mutual Information (PMI), and computational linguistics based Distributional Affix Mining (DAM). Using a Hausa Ajami Bible corpus consisting of 637,414 tokens, AjamiMorph identifies 1,611 high-confidence morphemes, achieving 99.9{\%} coverage. The inventory exhibits a linguistically realistic distribution (66.0{\%} stems, 22.6{\%} suffixes, 11.4{\%} prefixes) and recovers 77.8{\%} of known Hausa affixes. A permutation test that shuffles method assignments (preserving per-method selection sizes) confirms that the observed agreement is above-chance; chi-square remains as a secondary check. A lightweight 5-gram LM comparison (characters vs. consensus morphemes) provides an extrinsic signal. We also report negative results for script-driven Arabic assumptions and LLM-first annotation. This work provides the first unsupervised morpheme inventory for Hausa Ajami and demonstrates consensus as a robust strategy for zero-resource morphology."
}