TajikNLPWorld – Persian NLP & Low‑Resource Languages Research Hub

TajikNLPWorld is a collaborative research initiative dedicated to advancing natural language processing for Tajik, Persian/Dari, and low‑resource languages in the Iranian language family. We develop state‑of‑the‑art language models, machine translation systems, linguistic resources, and educational tools to empower under‑represented languages in the digital age.

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🎯 Our Mission

• Build open‑source language models for Tajik and other Persian varieties (Dari, Hazaragi).
• Create high‑quality linguistic resources (corpora, lexicons, evaluation benchmarks).
• Advance machine translation between Tajik, Persian, Dari, and major world languages.
• Develop educational materials and interactive demos to lower the entry barrier for low‑resource NLP.
• Foster a community of researchers, developers, and native speakers working together on language technology.

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🚀 Interactive Demos

Explore our live Hugging Face Spaces and try out our models directly in your browser:

🔤 Language Models

• TajikGPT Playground – Generate and analyze Tajik text with our latest causal LM.
• PersianBERT Explorer – Masked language modelling for Tajik, Persian, and Dari.
• Multilingual Embeddings – Compare word/sentence vectors across Iranian languages.

🌐 Machine Translation

• Tajik ↔ Persian Translator – Neural translation between Tajik and Persian (Farsi).
• Tajik ↔ Russian Translator – Translation demo for Central Asian context.
• Persian Multi-Dialect Translation – Translate between Tajik, Dari, and Iranian Persian.

📚 Linguistic Tools

• Tajik Morphological Analyzer – Interactive segmentation and POS tagging (Cyrillic & Perso-Arabic scripts).
• Named Entity Recognition for Tajik – Identify persons, locations, organizations.
• Script Converter – Convert between Cyrillic Tajik and Perso-Arabic script.

📊 Data & Benchmarks

• Tajik Corpus Explorer – Browse and query our curated text collections.
• Persian NLP Leaderboard – Compare model performance on Tajik, Persian, and Dari tasks.
• Annotation Tools – Help us improve datasets with your feedback.

Click on any demo to start experimenting – no installation required!

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🧠 Research Focus Areas

🏔️ Tajik Language Technologies

• Creation of the first large‑scale pretrained models for Tajik (both Cyrillic and Perso-Arabic scripts).
• Morphological disambiguation and syntactic parsing for Tajik.
• Speech recognition and synthesis for Tajik (coming soon).

📜 Persian & Iranian NLP

• Cross‑dialectal transfer learning among Tajik, Dari, and Iranian Persian.
• Unified tokenization and subword models for the Persian language continuum.
• Machine translation between Persian varieties and major languages.

📉 Low‑Resource NLP

• Data augmentation and semi‑supervised learning techniques.
• Leveraging multilingual models (e.g., mT5, XLM‑R) for under‑represented languages.
• Few‑shot and zero‑shot learning for tasks like NER and sentiment analysis.

🤖 Language Models

• Pretraining from scratch and continued pretraining on Persian/Tajik corpora.
• Efficient architectures (ALBERT, DistilBERT) for low‑resource settings.
• Evaluation and bias analysis of Persian language models.

📖 Linguistic Resources

• Corpora: News, literature, web‑crawled texts, social media.
• Lexicons: Morphological dictionaries, wordnets, sentiment lexicons.
• Benchmarks: Named entity recognition, part‑of‑speech tagging, machine translation test sets.

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📦 Models & Datasets

We release all our models and datasets on Hugging Face Hub under open licenses.

More models and datasets are added regularly. Follow our organization page for updates.

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📚 Educational Resources

We believe in open education and reproducible research. All our tutorials and teaching materials are freely available.

• Interactive Notebooks – Hands‑on tutorials for building low‑resource NLP systems (in Python, using Hugging Face libraries).
• Video Lectures – Recorded talks on Persian/Tajik NLP, data collection, and model training.
• Course Materials – Slides, readings, and assignments from our university courses.
• Blog Posts – Deep dives into challenges and solutions for Tajik and Persian languages.

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📝 Selected Publications

1. "TajikBERT: A Pretrained Language Model for Tajik in Cyrillic and Perso-Arabic Scripts" – LREC 2024
2. "Bridging Dialects: Machine Translation for Tajik, Dari, and Persian" – WMT 2023
3. "Building a Named Entity Recognition Dataset for Tajik" – IranNLP 2023
4. "Multilingual Representations for Iranian Languages: A Comparative Study" – EMNLP 2022
5. "Tajik Corpus: Collection, Annotation, and Baseline Experiments" – Dialogue 2022

Full list with links to PDFs available on our Publications Page.

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🤝 Get Involved

We welcome contributions from the community – whether you are a researcher, developer, student, or native speaker.

For Researchers

• Use our models and datasets in your work (and cite us!).
• Collaborate on joint papers and grant proposals.
• Contribute new benchmarks or evaluation tasks.

For Developers

• Integrate our models into your applications.
• Report bugs or suggest improvements via GitHub Issues.
• Submit pull requests to our open‑source repositories.

For Native Speakers & Linguists

• Help us validate translations and annotations.
• Share texts or corpora (with permission) to enrich our data.
• Provide feedback on model outputs to reduce errors.

For Students

• Use our demos and tutorials for learning.
• Participate in our mentorship program or summer schools.
• Start your own research project with our support.

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🌐 Connect With Us

• 🤗 Hugging Face: TajikNLPWorld – Models, datasets, and spaces.
• 💻 GitHub: TajikNLPWorld – Source code, development, and issue tracking.
• 📧 Email: contact@tajiknlp.world – General inquiries and collaboration.
• 🐦 Twitter/X: @TajikNLP – News and updates.
• 📝 Blog: Medium/TajikNLPWorld – In‑depth articles.

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🔄 Ecosystem Integration

Our work is integrated with the broader Hugging Face ecosystem:

• Models on the Hub with easy‑to‑use pipelines.
• Datasets with streaming and evaluation scripts.
• Spaces for interactive demos and educational tools.
• Gradio apps for user‑friendly interfaces.

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Empowering Tajik and Persian languages through open science and community collaboration.