mmdt-tokenizer 0.1.3

Myanmar Text Segmenter

Grammar-based Text Segmentation

The mmdt-tokenizer is designed with a grammar-oriented approach to Myanmar text segmentation. It models tokenization through the grammatical structure of the language, particularly the use of postpositions, particles, and predicate constructions.

Core Principles

Pattern Protection

Before segmentation, special patterns such as URLs, numbers, emails, and date formats are temporarily protected to prevent accidental splitting during tokenization.

Grammar-driven lexicons

Lexicons are built around grammatical categories such as postpositions, conjunctions, sentence-final particles, auxiliary verbs, and negation markers. Each entry is syllable-based, allowing flexible matching and better handling of morphological variations.

Pipeline-based rule segmentation

The tokenization process passes through a defined sequence of grammatical matchers (e.g., POSTP, AUX, SFP, NEG), which reflect the syntactic order of Myanmar sentences.

Structural merging

Rules like merge_predicate() combine related chunks (e.g., verb + auxiliary + negation + particle) into coherent grammatical units, producing more linguistically meaningful tokens.

Extensible design

The system is designed to grow with additional grammatical patterns and lexicon types without retraining, making it adaptable for both general text and domain-specific applications.

Summary

This approach enables mmdt-tokenizer to segment Myanmar text based on grammar and structure — resulting in context-aware tokenization that aligns with natural language syntax.

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Features

• Normalize Myanmar text (remove unwanted spaces, support space removal modes) (Developed by NW)
• Tokenize into syllables (Developed by NW)
• Protection (Developed by NW)
• Tokenize into words using grammar-rules (Developed by Myo)
• Optionally save tokenization results to CSV (Developed by NW)

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Credit & Inspiration

This library draws inspiration from the oppaWord: Myanmar Word Segmenter by Ye Kyaw Thu. The license of oppaWord is MIT.

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Folder Structure

src/
└── mmdt_tokenizer/
    ├── __init__.py
    ├── core.py
    │
    ├── data/
    │
    ├── preprocessing/
    │   ├── __init__.py
    │   ├── cleaner.py
    │   ├── normalizer.py
    │   ├── preprocess.py
    │   └── protector.py
    │
    ├── rule_segmenter/
    │   ├── __init__.py
    |   ├── cleaner.py
    │   ├── collapse.py
    │   ├── engine.py
    │   ├── lexicon.py
    │   ├── merge_ops.py
    │   ├── scanner.py
    │   └── types.py
    │
    ├── tokenizer/
    │   ├── __init__.py
    │   ├── syllable_tokenizer.py
    │   └── word_tokenizer.py
    │
    ├── utils/
    │   ├── __init__.py
    │   ├── config.py
    │   ├── csv_utils.py
    │   ├── data_utils.py
    │   └── patterns.py
    │
    ├── scripts/
    │   ├── build_lexicons.py
    │   └── build_lexicons.ipynb
    │
    └── tests/
└─ pyproject.toml
└─ LICENSE    
└─ README.md

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Folder	Purpose
data/	Holds raw and formatted datasets, lexicon CSVs, and output files.
preprocessing/	Handles text cleaning, normalization, and input preparation.
rule_segmenter/	Core rule-based segmentation logic, including lexicon operations and chunk merging.
tokenizer/	Contains syllable-level and word-level tokenizers.
utils/	Utility functions — CSV and data handling, text patterns, configs, and helpers.
scripts/	Developer utilities and notebooks (e.g., lexicon builder).
tests/	Unit and integration test cases for validation.
core.py	Main entry module coordinating tokenization and pipeline components.

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Installation

pip install mmdt-tokenizer

Usage Example

from mmdt_tokenizer import MyanmarTokenizer

tokenizer = MyanmarTokenizer()

text = "သူသွားမယ်သို့မဟုတ်သူလာမယ်။"
tokens = tokenizer.word_tokenize(text)

print(tokens)
# Expected Output: ["သူ", "သွားမယ်", "သို့မဟုတ်", "သူ", "လာမယ်။"]

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License

Distributed under the MIT License. See LICENSE for more information.

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Changelog / Versioning

v0.1.0 — initial release with core tokenization features