boffire/tatoeba-kabyle-audio
Tatoeba Kabyle Audio Dataset A clean, standardized audio-text dataset for Kabyle (Taqbaylit) automatic speech recognition, extracted from the Tatoeba Project and rigorously orthographically corrected. Dataset Description This dataset contains 47,789 Kabyle sentences with audio recordings (~25.78 hours total) sourced from Tatoeba. All transcriptions have been standardized to use correct Kabyle Latin characters, replacing visually similar false friends from Greek… See the full description on the dataset page: https://huggingface.co/datasets/boffire/tatoeba-kabyle-audio.
Tatoeba Kabyle Audio Dataset
A clean, standardized audio-text dataset for Kabyle (Taqbaylit) automatic speech recognition, extracted from the Tatoeba Project and rigorously orthographically corrected.
Dataset Description
This dataset contains 47,789 Kabyle sentences with audio recordings (~25.78 hours total) sourced from Tatoeba. All transcriptions have been standardized to use correct Kabyle Latin characters, replacing visually similar false friends from Greek, Cyrillic, and other Latin scripts that commonly contaminate Kabyle text corpora.
Character Standardization
Kabyle uses the following Latin characters in its standard orthography:
ɛ(U+025B) /Ɛ(U+0190) — open-mid front unrounded vowelɣ(U+0263) /Ɣ(U+0194) — voiced velar fricativeč(U+010D) /Č(U+010C) — voiceless postalveolar affricateǧ(U+01E7) /Ǧ(U+01E6) — voiced postalveolar affricateḥ(U+1E25),ḍ(U+1E0D),ṛ(U+1E5B),ṭ(U+1E6D),ṣ(U+1E63),ẓ(U+1E93) — emphatic/pharyngeal consonants
These are frequently confused with visually similar characters in raw web data. This dataset applies the following corrections:
Additionally, Unicode NFC normalization is applied to resolve precomposed vs. decomposed forms (e.g., z + combining dot below → ẓ).
3,643 sentences (7.62%) required at least one character fix.
Audio Statistics
The audio consists of short, read-aloud sentences typical of the Tatoeba project. The tight duration distribution (most clips are 1–3 seconds) makes this dataset well-suited for Wav2Vec 2.0 CTC training with minimal memory overhead.
File Sizes
Splits
Features
sentence_id: Tatoeba sentence IDtext_raw: Original transcription from Tatoeba (before cleaning)text: Cleaned, standardized Kabyle transcriptionaudio: Audio waveform (16 kHz, mono)character_fixed: Boolean flag indicating whether a false-friend fix was applied
Usage
from datasets import load_dataset
ds = load_dataset("boffire/tatoeba-kabyle-audio")
sample = ds["train"][0]
print(sample["text"])
# → standardized Kabyle sentenceCitation
If you use this dataset, please cite the Tatoeba Project:
@misc{tatoeba,
title = {Tatoeba: Collection of sentences and translations},
howpublished = {\url{https://tatoeba.org}},
}License
Audio files and sentences from Tatoeba are licensed under CC BY 4.0 (or compatible individual licenses as noted in the original Tatoeba metadata).
Acknowledgments
- Tatoeba Project contributors
- Dataset prepared by boffire
