mlsanityData to 7 Oct 2026

TajikNLP: An Open-Source Toolkit for Comprehensive Text Processing of Tajik (Cyrillic Script)

arXiv 2605.04583 ↗First posted 6 May 2026cs.CLcited by 1

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Abstract (arXiv)

The Tajik language, written in Cyrillic script, remains severely under-resourced in terms of publicly available natural language processing (NLP) toolkits, hindering both linguistic research and applied development. This paper introduces TajikNLP, an open-source Python library that provides the first comprehensive pipeline for processing authentic Tajik text while preserving the original Cyrillic orthography. The library implements a modular architecture centered around a unified Doc object, enabling sequential application of components for cleaning, normalization, tokenization (including subword BPE), morphemic segmentation, part-of-speech tagging, stemming, lemmatization, and sentence splitting. A novel unified morphology engine is introduced, offering controlled and deep analysis modes that significantly improve handling of Tajik's agglutinative nominal and verbal inflections. The release further incorporates a lexicon-based sentiment analyser and pre-trained Word2Vec/FastText embeddings loaded directly from the Hugging Face Hub. To ensure reproducibility and facilitate future research, four accompanying linguistic datasets -- a POS-tagged corpus (52.5k entries), a sentiment lexicon (3.5k entries), a toponym gazetteer (5.6k entries), and a personal names dataset (3.8k entries) -- have been openly published under permissive licenses. The library's reliability is validated by an extensive test suite of 616 automated tests achieving 93% source code coverage. TajikNLP thus establishes a foundational technological infrastructure for Tajik language processing, lowering the barrier to entry for both academic and industrial applications in low-resource Cyrillic-script environments.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 21 references that are in the map. First posted on arXiv 6 May 2026.

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5 of 21 references.

References · 5

  1. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  2. 2025Connecting the Persian-speaking World through Transliterationcited by 4
  3. 2025ParsTranslit: Truly Versatile Tajik-Farsi Transliterationcited by 4
  4. 2026FreeTxt-Vi: A Benchmarked Vietnamese-English Toolkit for Segmentation, Sentiment, and Summarisationcited by 3
  5. 2025Low-Resource, High-Impact: Building Corpora for Inclusive Language Technologiescited by 2

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