TugaLex 🗣️

TugaLex is a comprehensive lexicon handler and linguistic utility for Portuguese dialects. It provides deep data on phoneme transcription (IPA), syllable segmentation, and historical/modern orthographic rules.

Designed for NLP pipelines and linguistics research, it allows you to handle the complexities of Portuguese across different regions and historical agreements with a unified API.

🌍 Supported Dialects

TugaLex maps standard ISO codes to internal regional datasets:

✨ Key Features

1. Phonemes & Syllables

Retrieve IPA transcriptions and syllable breaks based on the word's Part-of-Speech (POS) and specific region.

from tugalex import TugaLexicon

lex = TugaLexicon()

# Get both syllables and phonemes
info = lex.get("acordo", pos="NOUN", region="lbx")
# Output: {'syllables': ['a', 'cor', 'do'], 'phonemes': 'ɐˈkoɾdu'}

# POS matters!
verb_phonemes = lex.get_phonemes("acordo", pos="VERB")
# Output: 'ɐˈkɔɾdu'
verb_phonemes = lex.get_phonemes("acordo", pos="NOUN")
# Output: 'ɐˈkoɾdu'

2. Orthographic Agreement (AO1990)

Effortlessly convert text between pre-agreement and post-agreement (AO1990) standards for both Portugal and Brazil.

• Normalize: Old spelling → Modern spelling.
• Reverse: Modern spelling → Old regional spelling (PT or BR).

normalized = lex.normalize_ao1900(sentence)

3. Linguistic Insights

TugaLex identifies specific linguistic phenomena programmatically:

• Homographs: Words that change pronunciation based on POS (e.g., sede (thirst) vs sede (headquarters)).
• Archaic Words: Mapping 19th-century etymological spellings to modern ones.
• Silent Letters: Identifying words with silent 'p' or 'c' common before the 1990 agreement.
• Voiced 'u': Detecting words where 'u' is pronounced in 'gue/gui/que/qui' clusters (formerly marked with a trema ü).

📂 Datasets

TugaLex ships the following datasets which contain over 100,000 entries sourced from the Portal da Língua Portuguesa.

• regional_dict.csv: Phoneme and syllable mappings.
• heterophonic_homographs.csv: words pronounced differently depending on postag.
• acordo_ortografico_pt_PT.csv: Portugal old orthographic spellings.
• acordo_ortografico_pt_BR.csv: Brazil old orthographic spellings.
• archaisms.csv: normalized words from before the 20th century.