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arXiv Computation and Language By Mohamed-Amine Chadi, Ezzahra Ait El Arbi, Ismail Khayoub, Aymane Fadili, Yassine Ennhili, Jadjigua Bouali, Hanane Inhid, Mohammed Ameksa, Hajar Mousannif

TutlAit v1: a crowdsourced Moroccan Tamazight speech dataset with Arabic transcriptions and regional accent labels

Read the original on arXiv Computation and Language →

The TutlAit v1 dataset is a crowdsourced corpus of Moroccan Tamazight speech paired with Modern Standard Arabic transcriptions and explicit regional accent labels. It contains 13,384 audio files (≈20.9 hours) collected via a web application, with volunteers contributing through text‑to‑audio and audio‑to‑text workflows, and includes additional segments from freely available media. The dataset covers Atlas, Souss, Rif, and Kabyle varieties, making it a valuable resource for speech recognition, translation, and accent identification in an under‑resourced language.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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