⚙️ Installation

pip install ruby

✨ What is good about RUBY?

• Rule-based, deterministic translation; unlike Google Translate - giving only 1 non-deterministic result
• Using NLTK parsing interface and is built on top of already-efficient NLTK backend
• Can be used for data augmentation

📖 Usage

from ruby import Translator

# Source sentence to be translated
src_sentences = ["I love good dogs", "I hate bad dogs"]

# Source grammar in nltk parsing style
src_grammar = """
                S -> NP VP
                NP -> PRP
                VP -> VB NP
                NP -> JJ NN
                PRP -> 'I'
                VB -> 'love' | 'hate'
                JJ -> 'good' | 'bad'
                NN -> 'dogs'
                """

# Some edit within source grammar to target grammar
src_to_target_grammar =  {
    "NP -> JJ NN": "NP -> NN JJ" # in Vietnamese NN goes before JJ
}

# Word-by-word dictionary from source language to target language
en_to_vi_dict = {
    "I":"tôi",
    "love":"yêu",
    "hate":"ghét",
    "dogs":"những chú_chó",
    "good":"ngoan",
    "bad":"hư"
    }

translator = Translator(src_grammar = src_grammar,
                        src_to_tgt_grammar = src_to_target_grammar,
                        src_to_tgt_dictionary = en_to_vi_dict)

trans_sentences = translator.translate(src_sentences) 
# This should returns ['tôi yêu những chú_chó ngoan', 'tôi ghét những chú_chó hư']

⚖️ License

This repository is using the Apache 2.0 license that is listed in the repo. Please take a look at LICENSE as you wish.

✍️ BibTeX

If you wish to cite the framework feel free to use this (but only if you loved it 😊):

@misc{phat2020ruby,
  author = {Truong-Phat Nguyen},
  title = {RUBY: Universal Rule-Based Machine Translation NLP toolkit},
  year = {2020},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/nlp-ruby/ruby}},
}

Contributors:

• Patrick Phat Nguyen