This release is a pre-release and may not be stable for production use.
arbtok
Rule-based Arabic (MSA) text→IPA with tashkeel diacritization — a downstream Arabic engine built on orthography2ipa.
Word phonology is built on the orthography2ipa shared lattice: the
language-agnostic grapheme tokenizer (PhonetokTokenizer) over the ar
spec grapheme table produces a per-position candidate lattice. The ar
engine (orthography2ipa ≥ 1.70) handles the segment-local phonology
natively — gemination (shadda ّ, glides included), lam-alif / presentation
ligatures (ﻻ → laː), onset glides (يَ → ja), a hamza carrier's bare
/ʔ/ before an explicit harakah, a fatḥa + standalone alif maksūra as one
long vowel (حَتَّى → ħattaː), a sukūn-final coda glide (ظَبْي → ðˤabj,
رَمْي → ramj, while فِي stays fiː), and pausal tāʾ marbūṭa. The last two
were once patched by arbtok's own MaterLectionisRescorer /
GlideCodaRescorer; orthography2ipa 1.70 (upstream #251) fixed them at
source, so those rescorers are gone. The Arabic morpho-phonology that the
shared table still cannot express is layered on as composable
LatticeRescorers (arbtok/lattice.py) rather than a private tokenizer
fork:
- sun-letter assimilation (idghām ash-shamsiyya) — the lām of the
definite article ⟨ال⟩ assimilates into a following coronal (sun) letter
(
al-šams→aš-šams); moon letters keep the lām (al-qamar); - hamzat al-waṣl elision — a word-initial prosthetic alif is silent,
its harakah carrying the vowel (
istiqbāl); - accusative-alif silencing after tanwīn al-fatḥ (
marħaban), and the bare glottal stop of a hamza carrier before a sukūn or word edge (taʔθīr).
Emphatic (pharyngealization) spreading rides on the ar spec's own B8
allophone_rules. Cross-word sandhi — clitic joining, cross-word waṣl
elision, tanwīn pausal forms, tāʾ marbūṭa, and idgham/iqlab nasal
assimilation — is orthogonal to the word lattice and lives in the
sentence-level orchestration. orthography2ipa 1.70 also added a shared
sentence-context seam (orthography2ipa.sentence: SentenceLattice +
SentenceRescorer with prev_word/next_word edge slots and
is_phrase_final), the sanctioned home for that cross-word layer; arbtok's
migration of its space-boundary waṣl elision and tanwīn pausal forms onto
the seam is in progress (see docs/ and the tracking notes). Bare
(undiacritized) text is diacritized
first via text2tashkeel —
a model picker over bundled ONNX diacritization models.
Honesty note: the gold IPA reference set was LLM-generated and has not been validated by a native MSA speaker. If you speak MSA, pull requests are very welcome.
Installation
pip install arbtok
Usage
arbtok is built on orthography2ipa
(spec data and the shared G2PPlugin/WordContext base types) and owns the
Arabic pipeline — orthography2ipa stays the language-agnostic base library.
Engine class
from arbtok.tokenizer import Sentence
Sentence("اَلسَّلَامُ عَلَيْكُمْ").ipa
An isolated MSA word transcribes on the shared lattice directly:
from arbtok.lattice import word_ipa
word_ipa("الشَّمْس") # 'aʃʃams' — sun-letter assimilation as a rescorer
word_ipa("الْقَمَر") # 'alqamar' — moon-letter control (lām kept)
Bare text is handled by diacritizing first:
from arbtok.plugin import ArbtokG2PPlugin
plugin = ArbtokG2PPlugin()
plugin.transcribe("كتاب جميل") # auto-tashkeel + IPA
Diacritization only
from arbtok.tashkeel import TashkeelDiacritizer # wraps text2tashkeel
TashkeelDiacritizer().diacritize("كتاب جميل")
Quality benchmarks
The test suite pins a gold sentence set (CER target ≤ 5% against the
reference transcriptions) and benchmarks against espeak-ng. See
tests/test_ipa_fuzzy.py and docs/ for details.
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