abdelhaqueidali/Kabyle-Latin-to-Tifinagh-Parallel-Corpus

Dataset Card for Kabyle Latin-to-Tifinagh Parallel Corpus

This dataset provides a parallel corpus of the Kabyle language ($\text{Taqbaylit}$), pairing native Latin-based orthography with automated, context-aware Neo-Tifinagh transliterations. It is built by processing clean source sentences through an algorithmic engine designed to preserve grammar structures and protect foreign loanwords.

Dataset Details

Dataset Sources

• Repository: [More Information Needed]
• Source Project: Tatoeba Translation Corpus

Uses

Direct Use

• Training and fine-tuning machine translation models (e.g., Latin-to-Tifinagh tokenizers).
• Building automated transliteration tools and orthographic normalizers for Amazigh.

Out-of-Scope Use

This dataset is optimized specifically for standard latin orthography with slight modifications to get clearn Tifinagh orthography version.

Dataset Structure

The dataset consists of a tab-separated values (.tsv) file containing the following fields:

• Sentence ID: Unique identifier inherited from the Tatoeba database.
• Language Code: The ISO 639-3 code for Kabyle (kab).
• Tifinagh Text: The processed Neo-Tifinagh transliteration column.
• Latin Text: The original source Kabyle sentence written in the standard Latin script.

Dataset Creation

Curation Rationale

While the Kabyle language is widely written using a modified Latin alphabet, Neo-Tifinagh holds official and cultural prominence in the region of North Africa. This dataset bridges the script divide algorithmically, creating a high-fidelity parallel text repository that filters out foreign names and isolates native phonetic behaviors.

Source Data

Data Collection and Processing

The underlying source sentences are pulled from the Kabyle subset of the Tatoeba project. The text was passed through a specialized Python processing pipeline applying several linguistic constraints:

• Grammatical Suffix Merging: Structural dashes (-) used for indirect objects, prepositions, or kinship suffixes (e.g., fell-ak, baba-s, tama-m) are cleanly removed and merged into a single word token (yielding ⴱⴰⴱⴰⵙ instead of ⴱⴰⴱⴰ ⵙ). All other structural punctuation dashes are globally normalized to spaces.
• Contextual Schwa ($\mathbf{e}$ / ⴻ) Optimization: The engine automatically strips the schwa (ⴻ) if it appears at the absolute beginning of a word. Internally, it strips ⴻ when sandwiched between two different consonants, but strictly preserves it between identical consonants.
• Foreign Word Isolation: To prevent phonetic corruption of loanwords as much as possible, the system flags and skips transliteration entirely (keeping words in Latin script) if a token meets any of these criteria:
  • Contains French/Foreign accented vowels (é, è, à, etc.).
  • Contains the vowel o or O.
  • Terminates with the letter e or E.
  • Is an all-caps acronym (e.g., MRI, M.R.I.).
  • Contains a standalone uppercase letter inside or at the end of a sentence (e.g., vitamins like C).
• Targeted Bypasses: Standalone instances of high-frequency words like Ait/ait are explicitly targeted to resolve to ⴰⵢⵜ. Ubiquitous name patterns common in Tatoeba text like Tom, tom, Ṭom, and ṭum bypass the foreign letter filters and map directly to ⵟⵓⵎ.
• Direct Digraph Conversions: Common digraph inputs map explicitly to unified sounds without triggering foreign blocks (sh/ch $\rightarrow$ ⵙⵀ/ⵛⵀ, and ph $\rightarrow$ ⴼ).

Who are the source data producers?

The original source sentences are crowdsourced from independent contributors and native speakers on the open-source Tatoeba platform.

Personal and Sensitive Information

The source sentences consist of general conversational text, educational translations, and daily idioms. There is no intentionally collected private, personal, or sensitive information.

Bias, Risks, and Limitations

Because the script relies on a rule-based algorithmic filter to catch foreign structures, exceptional edge cases might slip through:

• A native word spelling that happens to match an accidental foreign filter rule could remain in Latin text.
• Unusual foreign names missing the standard vowel markers (o, trailing e, accents) might be forcefully transliterated into Tifinagh incorrectly.

Citation

BibTeX:

@misc{kabyle_latin_tifinagh_2026,
  title={Kabyle Latin-to-Tifinagh Parallel Corpus},
  author={Abdelhaque Id Ali},
  year={2026},
  publisher={Hugging Face Hub}
}