README.md

metadata

license: cc0-1.0
language:
  - kab
language_bcp47:
  - kab-Latn
size_categories:
  - 10K<n<100K
task_categories:
  - token-classification
task_ids:
  - lemmatization
pretty_name: KabG2P — Kabyle grapheme-to-phoneme pronunciation dictionary
tags:
  - kabyle
  - taqbaylit
  - berber
  - tamazight
  - low-resource
  - grapheme-to-phoneme
  - g2p
  - pronunciation
  - phonetics
  - ipa
  - text-to-speech
  - automatic-speech-recognition
configs:
  - config_name: default
    data_files:
      - split: train
        path: default/train.jsonl

KabG2P

A grapheme-to-phoneme pronunciation dictionary for Kabyle (Taqbaylit, kab, Latin script), from the AƔBALU project.

25,634 Kabyle word–IPA pairs recovered by aligning 292,921 tokens across 59,462 sentence pairs at a 99.53% alignment rate, with a 0% ambiguity rate across the entire vocabulary. Every attested word has exactly one IPA reading. It is the phonetics layer underlying agbalu/Matoub-TTS and agbalu/Fadhma-300M, and the reference target for any Kabyle G2P model.

from datasets import load_dataset

ds = load_dataset("agbalu/KabG2P", split="train")

print(ds[4])
# {
#   "word":     "ababat",
#   "ipa":      "æβæβæθ",
#   "variants": [{"ipa": "æβæβæθ", "count": 10}],
#   "repaired": False
# }

Data

split	rows	source tokens
train	25,634	292,921

Eight entries whose headword falls outside the Kabyle writing system (3d, androïd, mp3, muḥ€nd, rosé, supermarché, xelleṣ̣, ṭeyyeb‟) are present in the source lexicon with correct IPA but are excluded from this release; G2P benchmarking on non-Kabyle words is not meaningful.

Schema

field	type	description
word	str	Canonical Kabyle Latin spelling, NFC-normalised
ipa	str	IPA transcription — the majority pronunciation across aligned tokens
variants	list[dict]	Frequency-sorted alternative readings: [{"ipa": "...", "count": N}, ...]
repaired	bool	true where this project restored a character the upstream source dropped

IPA Phoneme Inventory

42 phoneme symbols in the source; 38 appear in 3 or more entries. The full inventory of symbols observed across 292,921 aligned tokens:

category	symbols
Vowels	æ ɑ ə i u
Stops (plain)	b d ɡ k t p
Stops (emphatic)	dˤ
Fricatives (plain)	β ð ʝ ç θ f s z ʃ ʒ x χ ʁ ħ ʕ h
Fricatives (emphatic)	ðˤ
Affricates	t͡ʃ
Nasals	m n ɲ ŋ
Liquids	r l
Glides	j w
Length mark	ː

Phonological Rules

Three conditioned rules are applied and verified against the aligned data:

1. Spirantization by gemination. Singleton b d g k t ḍ → fricatives β ð ʝ ç θ ðˤ; geminates → stops b d ɡ k t dˤ. Count agreement is exact for t, b, and k across 292,921 tokens; off by one for g.

2. Vowel backing beside emphatics and uvulars. a → ɑ when adjacent to ḍ ṣ ṭ ẓ ṛ q ɣ x. The rule is 92.44% accurate against an 87.19% always-æ baseline — +5.25 pp.

3. i/u laxing is not applied. The only recoverable conditioning environment (closed syllable) scored 75.59% against a 74.99% baseline — below the threshold for inclusion. Attested words carry their verified allophones from this dictionary; out-of-vocabulary words receive the tense vowel.

Benchmark Baseline

The AƔBALU rule-based G2P system achieves 78.18% exact-match rate on this dictionary without any dictionary lookup — purely from spelling rules. This is the floor any learned G2P model must exceed, and the dictionary itself is the training target and ceiling.

Repaired Entries

The upstream generator drops any character it has no rule for, silently producing a shorter IPA string. This release repairs 199 entries, flagged by repaired: true:

character	affected words	repair
o	128	bob → ββ repaired to βoβ
ţ U+0163	73	aţan → ææn repaired to ætːæn (geminate, from corpus evidence)
é, ï	3	left as-is (outside the writing system)

🔴 ţ is attested Kabyle. It is the Dallet-tradition spelling for the spirantised t, occurring 21,058 times in AƔBALU-Text v1 and in 1,407 word types. It is repaired to the geminate on corpus evidence. No audio confirms this mapping — ţ does not appear in Common Voice Kabyle — and the repair is disclosed rather than hidden.

Usage

from datasets import load_dataset

g2p = load_dataset("agbalu/KabG2P", split="train")
g2p[0]
# {'word': 'a', 'ipa': 'æ', 'variants': [{'ipa': 'æ', 'count': 2644}], 'repaired': False}

lookup = {row["word"]: row["ipa"] for row in g2p}
lookup["azul"]

No word takes two transcriptions. variants records how often each spelling of the pronunciation was seen while aligning, and in all 25,634 entries the winner is the only entry — so a plain dictionary is a faithful representation, not a lossy one.

repaired marks the 199 entries where the upstream generator dropped a character it had no rule for and this build restored it. Filter on it to see exactly which:

g2p.filter(lambda row: row["repaired"])

Orthography

All headwords are normalised to canonical Kabyle Latin script under normaliser 1.3.0+rules1.0.0 (81 rules). 199 entries carried Greek homoglyphs (ε γ Σ Γ Ԑ) in the upstream source and were corrected to canonical ɛ ɣ Ɛ Ɣ Ɛ. The repaired field records every affected entry.

Source

field	value
Upstream	boffire/kabyle-g2p-training-data
Upstream licence	CC0-1.0
Sentences aligned	59,462 (59,185 successfully aligned)
Alignment rate	99.53%
Ambiguity rate	0.00%
Normaliser version	1.3.0+rules1.0.0
Repaired entries	199

Citation

@misc{agbalu_kabg2p,
  title  = {KabG2P: a Kabyle grapheme-to-phoneme pronunciation dictionary},
  author = {AƔBALU},
  year   = {2026},
  url    = {https://huggingface.co/datasets/agbalu/KabG2P}
}

Please also cite the upstream source: boffire/kabyle-g2p-training-data.

Licence

CC0-1.0. The upstream source (boffire/kabyle-g2p-training-data) is CC0-1.0. The repairs and normalisation applied by this project are released under the same licence.

Part of AƔBALU, a Kabyle corpus and model collection.