CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus

Understand

Spoken language translation has recently witnessed a resurgence in popularity, thanks to the development of end-to-end models and the creation of new corpora, such as Augmented LibriSpeech and MuST-C.

• Existing datasets involve language pairs with English as a source language, involve very specific domains or are low resource.
• We introduce CoVoST, a multilingual speech-to-text translation corpus from 11 languages into English, diversified with over 11,000 speakers and over 60 accents.
• We describe the dataset creation methodology and provide empirical evidence of the quality of the data.