punjabi-nlp-shahmukhi 0.1.1

Punjabi Shahmukhi NLP preprocessing toolkit

Punjabi NLP Toolkit 🇵🇰

A Python library for Punjabi (Shahmukhi + Roman) Natural Language Processing.

This toolkit is designed to handle real-world Punjabi text, including:

• Mixed script input (Roman + Shahmukhi)
• Noisy social media text
• Linguistic normalization

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🚀 Features

• ✅ Unicode & character normalization
• 🔄 Roman Punjabi → Shahmukhi conversion
• ✂️ Sentence & word tokenization
• 🚫 Stopword removal
• 📊 Frequency analysis
• 🔗 N-gram extraction (bigrams, trigrams)
• 🔍 Script detection (Shahmukhi / Gurmukhi / Roman)

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📦 Installation

pip install punjabi-nlp

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⚡ Quick Start

from punjabi_nlp import PunjabiPipeline

pipeline = PunjabiPipeline()

text = "mnu lagda ae tussi theek o"

output = pipeline.process(text)

print(output)

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🧪 Example Output

{
  'script': 'shahmukhi',
  'normalized_text': 'مینوں لگدا اے تسی ٹھیک او',
  'sentences': ['مینوں لگدا اے تسی ٹھیک او'],
  'tokens': ['مینوں', 'لگدا', 'اے', 'تسی', 'ٹھیک', 'او'],
  'token_count': 6,
  'frequency': {
    'مینوں': 1,
    'لگدا': 1,
    'اے': 1,
    'تسی': 1,
    'ٹھیک': 1,
    'او': 1
  }
}

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🔥 Mixed Script Example (Real-World Input)

text = "کِتّھے ایں؟ mnu lagda ae tussi theek o"

Output:

کتھے ایں? مینوں لگدا اے تسی ٹھیک او

👉 This demonstrates:

• Shahmukhi normalization
• Roman conversion
• Clean tokenization

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🧠 Why This Library?

Punjabi is a low-resource language in NLP, especially in Shahmukhi script.

This toolkit aims to:

• Provide a standard preprocessing pipeline
• Support linguistic research
• Enable corpus-based studies
• Handle code-mixed Punjabi text

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📊 Corpus Analysis

The library supports:

• Word frequency
• Bigrams & trigrams
• Lexical pattern extraction

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🏗️ Project Structure

punjabi_nlp/
├── normalization.py
├── tokenization.py
├── roman.py
├── stopwords.py
├── utils.py
├── corpus.py
└── pipeline.py

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🧩 Example Use Cases

• 📚 Corpus linguistics research
• 🧠 NLP model preprocessing
• 💬 Social media text cleaning
• 🗣️ Punjabi language tools
• 🎓 Teaching computational linguistics

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⚠️ Limitations

• Rule-based Roman conversion (not fully phonetic yet)
• Limited stopword list
• No POS tagging (planned)

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🚀 Future Work

• 🔁 Shahmukhi ↔ Gurmukhi transliteration
• 🧠 Smart phonetic Roman conversion
• 🏷️ POS tagging
• 📈 Named Entity Recognition (NER)
• 🖥️ GUI tool for live processing

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🤝 Contributing

Contributions are welcome!

You can help by:

• Improving normalization rules
• Expanding Roman mappings
• Adding datasets
• Reporting issues

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📜 License

MIT License

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👤 Author

Shoaib Tahir Computational Linguistics | Punjabi NLP

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⭐ Support

If you find this project useful:

• ⭐ Star the repository
• 📢 Share with others
• 🧠 Use in research

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