tugaphone — dialect-aware Portuguese phonemizer

tugaphone converts Portuguese text to IPA across all five Lusophone dialect groups. It combines a curated phonetic lexicon, meaning-based heterophone resolution via bifonia, and a scientifically- grounded regional-accent layer.

O gato dorme.
pt-PT → ˈu gˈa·tu ˈdoɾ·mɨ
pt-BR → ˈu gˈa·tʊ ˈdoɾ·mɪ
pt-AO → ˈu gˈa·tʊ ˈdoɾ·me
pt-MZ → ˈu gˈa·tu ˈdoɾ·me
pt-TL → ˈu gˈa·tʊ ˈdoɾ·me

Install

pip install tugaphone

30-second quick start

from tugaphone import TugaPhonemizer

ph = TugaPhonemizer()
print(ph.phonemize_sentence("O gato dorme.", "pt-PT"))
# ˈu gˈa·tu ˈdoɾ·mɨ ˈ···

TugaPhonemizer() loads the lexicon once; then call phonemize_sentence(text, lang) as many times as you like. Output is a space-separated phoneme string — one token per word — with ˈ marking primary stress and · marking syllable boundaries.

Features

Five dialect inventories

for code in ["pt-PT", "pt-BR", "pt-AO", "pt-MZ", "pt-TL"]:
    print(code, "→", ph.phonemize_sentence("Choveu muito ontem.", code))
# pt-PT → ʃu·ˈvew mˈũj·tu ˈõ·tẽ
# pt-BR → ʃo·ˈvew mwˈĩ·tʊ ˈõ·tẽ
# pt-AO → ʃo·ˈvew mˈũjn·tʊ ˈõ·tẽ
# pt-MZ → ʃu·ˈvew mˈũj·tu ˈõ·tẽ
# pt-TL → ʃo·ˈvew mˈuj·tʊ ˈõ·tẽ

Homograph disambiguation

Heterophonic homographs are resolved by meaning via bifonia: sede thirst vs HQ, forma mould vs shape, gosto noun vs verb. bifonia inserts open/closed-vowel diacritics that the grapheme rules read directly, so the same spelling can map to different pronunciations depending on sentence context.

print(ph.phonemize_sentence("Eu gosto de música."))   # verb → ˈgɔʃ·tu
print(ph.phonemize_sentence("Tenho bom gosto."))      # noun → ˈgoʃ·tu

Sub-regional accents

RegionalTransforms presets layer phonological rules on top of any dialect. Rules are grounded in published phonology (Cintra 1971; ALEPG). Every preset is reachable by its BCP-47 private-use code:

# Porto: stressed /o/ → [uo] (rising diphthong)
print(ph.phonemize_sentence("O vinho é muito bom.", "pt-PT-x-porto"))
# ˈu bˈi·ɲu ˈɛ mˈũj·tu bˈuõ ˈ···

# Açores: stressed /u/ → [y], l-palatalisation
print(ph.phonemize_sentence("O vinho é muito bom.", "pt-PT-x-azores"))
# ˈy vˈi·ɲu ˈɛ mˈỹj·tu bˈõ ˈ···

from tugaphone import list_dialects
print(list_dialects())   # all 20 registered codes

Available presets: NorthernDialect, PortoDialect, MinhoDialect, BragaDialect, FamalicaoDialect, FafeDialect, TrasMontanoDialect, CoimbraDialect, AlentejoDialect, AlgarveDialect, MadeiraDialect, AzoresDialect — importable from tugaphone.regional and passable as regional_dialect=, which overrides the code-derived preset.

Number normalization

Digits are spelled out with gender agreement and long/short scale per dialect:

from tugaphone.number_utils import normalize_numbers

normalize_numbers("vou comprar 1 casa")   # 'vou comprar uma casa'
normalize_numbers("vou adotar 1 cão")    # 'vou adotar um cão'
normalize_numbers("comprei 2 casas")     # 'comprei duas casas'

Syllabification and stress

Syllabification is handled by silabificador, registered as an orthography2ipa syllabifier plugin. Stress detection delegates to orthography2ipa's declarative StressRules.

Rules-only mode

Pass an IRREGULAR_WORDS-emptied dialect inventory to bypass the lexicon and use only grapheme rules — useful for testing rule coverage or synthesising unknown words.

orthography2ipa plugin interface

TugaphoneG2PPlugin implements orthography2ipa's G2PPlugin interface; SilabificadorSyllabifier implements its SyllabifierPlugin interface and is registered at the orthography2ipa.syllabify entry point.

from tugaphone.plugin import TugaphoneG2PPlugin

p = TugaphoneG2PPlugin(lang="pt-BR")
print(p.transcribe("o gato dorme"))   # ˈu gˈa·tʊ ˈdoɾ·mɪ

IPA is built word-by-word (no cross-word sandhi)

tugaphone builds a sentence's IPA from a character-level cascade: each CharToken.ipa composes into a GraphemeToken, graphemes into a WordToken.ipa, and Sentence.ipa is those word IPAs joined with spaces — each word transcribed independently. tugaphone does not route generation through orthography2ipa's pronunciation lattice (G2P.ipa_lattice) or its G2P.transcribe; it consumes only o2i's shared primitives (the PhonetokTokenizer grapheme trie, vowels classification, StressRules, and LanguageSpec loading) and applies its own dialect grapheme rules.

A consequence is that genuinely cross-word phonology is not modelled on the generation path. Standard European Portuguese external /s-sandhi — a word-final coda /s/ (isolated [ʃ]) voicing before a vowel-initial next word (os amigos → [ˈuz ɐˈmiɡuʃ], Mateus & d'Andrade 2000) — is not applied in the base pt-PT output (os stays [ˈuʃ]). The southern/insular presets' sibilant_voicing_sandhi is a per-token approximation: it voices a token's own final [ʃ]→[ʒ] when the word ends in <s>, with no visibility of the following word.

orthography2ipa (≥1.70) now carries this cross-word phonology natively — a declarative sandhi_rules set on the pt-PT spec (PT_FINAL_S_PREVOCALIC_VOICE → [z]; pt-PT-x-algarve/acores → [ʒ]) run through its SandhiEngine, and a SentenceRescorer / SentenceLattice sentence-context seam for boundary-aware rewrites. tugaphone cannot consume either today because neither its per-word IPA nor its lattice flows through o2i's G2P. Adopting the seam is a scoped follow-up (a "B6 stage-2" refactor) that routes sentence-level generation through o2i so cross-word sandhi is modelled once, upstream, instead of re-approximated per token. See docs/advanced.md.

Sibling libraries

tugaphone is part of the TigreGotico Portuguese NLP stack:

Documentation

• docs/quickstart.md — install, first call, dialect overview
• docs/dialects.md — five inventories and sub-regional accent presets
• docs/homographs.md — meaning-based disambiguation
• docs/numbers.md — number normalization and gender agreement
• docs/api.md — full class and function reference
• docs/tokenizer.md — the Sentence → Word → Grapheme → Character model
• docs/advanced.md — accents, serialization, integration

License

Apache License 2.0. See LICENSE.