dzoseg 0.1.3

A Dzongkha tokenizer and segmenter (32k Subword & Tseg)

dzoseg 🇧🇹

dzoseg is a lightweight Python library for Dzongkha text segmentation. It offers a hybrid approach, allowing users to choose between high-performance AI subword tokenization (using SentencePiece) and traditional Tseg-based segmentation.

🚀 Features

• Subword Segmentation: Uses a pre-trained Unigram model with a 32,000 vocabulary size for deep learning applications.
• Tseg Segmentation: A rule-based approach to split text into syllables based on the traditional Dzongkha Tseg (་).
• Zero-Dependency Logic: Simple to integrate into any NLP pipeline.
• Byte-Fallback: Automatically handles non-Dzongkha characters (English, numbers, etc.) without crashing.

📦 Installation

Install the package via pip:

pip install dzoseg


🛠 Usage
1. Subword (AI-Based) Segmentation
This method is recommended for Machine Learning tasks like machine translation or sentiment analysis.
from dzoseg import DzongkhaSegmenter

# Initialize the segmenter
ds = DzongkhaSegmenter()

text = "འབྲུག་རྒྱལ་གཞུང་གཙུག་ལག་སློབ་སྡེའི་འོག་ལུ་ཡོད་པའི་ཚན་རིག་དང་འཕྲུལ་རིག་མཐོ་རིམ་སློབ་གྲྭའི་གློག་རིག་དང་འཕྲུལ་རིག་ལས་ཁུངས།"

# Get subword tokens
tokens = ds.segment_subwords(text)
print(f"Subwords: {tokens}")

# Expected Output: 
# [' འབྲུག་', 'རྒྱལ་གཞུང་', 'གཙུག་ལག་སློབ་སྡེ', 'འི་', 'འོག་ལུ་ཡོད་པའི་', 'ཚན་རིག་', 'དང་', 'འཕྲུལ་རིག་', 'མཐོ་རིམ་སློབ་གྲྭ', 'འི་', 'གློག་རིག་', 'དང་', 'འཕྲུལ་རིག་', 'ལས་ཁུངས།']


2. Tseg-based Segmentation
This method splits the text strictly based on the Dzongkha syllable delimiter (Tseg).

# Get syllable-level tokens
syllables = ds.segment_tseg(text)
print(f"Syllables: {syllables}")

# Expected Output: 
# ['འབྲུག','རྒྱལ','གཞུང', 'ཙུག', 'ལག', 'སློབ', 'སྡེའི', 'འོག', 'ལུ', 'ཡོད', 'པའི', 'ཚན', 'རིག', 'དང', 'འཕྲུལ', 'རིག', 'མཐོ', 'རིམ', 'སློབ', 'གྲྭའི', 'གློག', 'རིག', 'དང', 'འཕྲུལ', 'རིག', 'ལས', 'ཁུངས།']

📊 Model Details
Model Type: Unigram (SentencePiece)
Vocabulary Size: "32,000"
Character Coverage: 100% (1.0)
Input Data: Cleaned Dzongkha Web & Literary Corpus
Byte Fallback: Enabled (True)

📂 Project Structure
dzoseg/
├── src/
│   └── dzoseg/
│       ├── models/
│       │   ├── dzo_unigram_32000.model
│       │   └── dzo_unigram_32000.vocab
│       ├── __init__.py
│       └── segmenter.py
├── examples/
│   ├── basic_usage.py
│   └── bulk_segmentation.py
├── pyproject.toml
└── README.md

📜 License
This project is licensed under the MIT License - see the LICENSE file for details.

Maintained by: Karma Wangchuk/https://github.com/KarmaCST/
Contact: [e-mail]