Meta Launches Omnilingual ASR Supporting Over 1,600 Languages

Automatic speech recognition (ASR) systems aim to make spoken language universally accessible by transcribing speech into text that can be searched, analyzed, and shared.

Currently, most automatic speech recognition systems focus on a limited set of high-resource languages that are well represented on the internet, often relying on large amounts of labeled data and human-generated metadata to achieve good performance.

This means high-quality transcriptions are often unavailable for speakers of less widely represented or low-resource languages, furthering the digital divide.

We're introducing Meta Omnilingual Automatic Speech Recognition, a suite of models providing automatic speech recognition capabilities for over 1,600 languages.