Sign in

UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data

By Chengyi Wang and others
In this paper, we propose a unified pre-training approach called UniSpeech to learn speech representations with both unlabeled and labeled data, in which supervised phonetic CTC learning and phonetically-aware contrastive self-supervised learning are conducted in a multi-task learning manner. The resultant representations can capture information more correlated with phonetic structures... Show more
June 10, 2021
=
0
Loading PDF…
Loading full text...
Similar articles
Loading recommendations...
=
0
x1
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Click on play to start listening