Each entry in the dataset consists of a unique MP3 and corresponding text file. Many of the <b>{ $hours }</b> recorded hours in the dataset also include demographic metadata like age, sex, and accent that can help train the accuracy of speech recognition engines.  The dataset currently consists of <b>{ $hours }</b> validated hours in <b>{ $languageCount }</b> languages, but we’re always adding more voices and languages. Take a look at our <languagesLink>Languages page</languagesLink> to request a language or start contributing.
Sekra n wayen ara ikecmen des tagrumma n yisefka d afaylu MP3 asuf akked ufaylu-is aḍris yemmenṭaḍen yid-s. Ddeqs seg <b>{ $hours }</b> n yisragen yettwaskelsen deg tagrumma n yisefka ad iseddu isefka ɣef tdimugrafit am uwtay (leɛmeṛ), tuzuft akked ususru i yezemren ad yefk afus i usluɣmu n tseddi n yimseddayen n uɛqal n taɣect.   Tagrumma n yisefka tamirant tegber <b>{ $hours }</b> n yisragen yettwaqeblen deg <b>{ $languageCount }</b> n tutlayin, maca aql-aɣ nrennu ugar n tuɣac akked tutlayin. Wali deg <languagesLink> usebter-nneɣ n tutlayin </languagesLink> akken ad tessutreḍ tutlayt neɣ ad tebduḍ attekki.