myspellchecker-resources

Build-time resources for myspellchecker - Myanmar language spell checker.

Overview

This repository hosts large binary files required by myspellchecker that are too large to bundle with the Python package. Files are downloaded automatically on first use.

Contents

segmentation/

• segmentation.mmap (100MB) - Memory-mapped dictionary containing unigram and bigram log probabilities for Myanmar word segmentation using Viterbi algorithm.

models/

• wordseg_c2_crf.crfsuite (3.2MB) - Conditional Random Fields model for syllable-based word tokenization.

curated_lexicon/

• curated_lexicon.csv - Curated Myanmar word list with POS tags for spell checking (57,566 entries).

This lexicon is built from the Myanmar Words List and the Ornagai dictionary. Data from the Ornagai dictionary was filtered and cleaned to produce a high-quality, consistent word list suitable for spell checking.

Lexicon Tag Distribution

Tag	Description	Count
N	Noun	49,836
ADJ	Adjective	3,130
V	Verb	2,630
ADV	Adverb	997
TN	Temporal Noun	231
ABB	Abbreviation	193
PRON	Pronoun	183
PART	Particle	122
INT	Interjection	116
CONJ	Conjunction	87
PPM	Post-Positional Marker	37
FW	Foreign Word	4
Total		57,566

Technical Notes

.bin to .mmap Conversion

The segmentation dictionary has been converted from pickle-based .bin files to memory-mapped .mmap format for:

• Memory Efficiency - Lazy loading without loading entire file into RAM
• Fork-Safe - Copy-on-Write (COW) semantics for multiprocessing
• Faster Startup - No pickle deserialization overhead
• Security - Eliminates pickle arbitrary code execution vulnerabilities
• Reduced Size - 100MB consolidated vs 315MB separate .bin files

Credits & Attribution

myWord Project

The word segmentation dictionary (segmentation.mmap) is derived from the myWord project:

• Repository: https://github.com/ye-kyaw-thu/myWord
• Author: Ye Kyaw Thu
• Description: Myanmar word segmentation using statistical methods with Viterbi algorithm

We are grateful to the myWord project for providing the foundational word frequency data that powers Myanmar text segmentation.

myTokenize Project

The CRF model and tokenization framework are based on the myTokenize library:

• Repository: https://github.com/ye-kyaw-thu/myTokenize
• Author: Ye Kyaw Thu

Curated Lexicon Sources

The curated lexicon (curated_lexicon.csv) is derived from the following sources:

• Ornagai Dictionary

  • Website: https://www.ornagai.com
  • Description: Comprehensive Myanmar-English dictionary. Data was filtered and cleaned to extract a consistent, high-quality word list.

• Myanmar Words List

  • Repository: https://github.com/myanmartools/myanmar-words
  • Description: Open-source Myanmar word collection.

We are grateful to all contributors for providing foundational data for Myanmar NLP.

Usage

Resources are downloaded automatically by myspellchecker:

from myspellchecker import SpellChecker

# Resources download automatically on first use
checker = SpellChecker()

Cache Location

Downloaded resources are cached at: ~/.cache/myspellchecker/resources/

License

These resources are provided under the same license terms as the original projects. Please refer to the original repositories for specific licensing information.