most citedLeveraging pre-trained representations to improve access to untranscribed speech from endangered languages

9 citations · 9 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CL2021★ 9 cited

Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages

Nay San, Martijn Bartelds, Mitchell Browne +9

Pre-trained speech representations like wav2vec 2.0 are a powerful tool for automatic speech recognition (ASR). Yet many endangered languages lack sufficient data for pre-training…