241 citations · 290 across the 15 of their papers we have counts for
4 papers · 2 filters
Introducing Semantics into Speech Encoders
Derek Xu, Shuyan Dong, Changhan Wang +10
Recent studies find existing self-supervised speech encoders contain primarily acoustic rather than semantic information. As a result, pipelined supervised automatic speech recogni…
Unified Speech-Text Pre-training for Speech Translation and Recognition
Yun Tang, Hongyu Gong, Ning Dong +8
We describe a method to jointly pre-train speech and text in an encoder-decoder modeling framework for speech translation and recognition. The proposed method incorporates four sel…
Towards End-to-end Unsupervised Speech Recognition
Alexander H. Liu, Wei-Ning Hsu, Michael Auli +1
Unsupervised speech recognition has shown great potential to make Automatic Speech Recognition (ASR) systems accessible to every language. However, existing methods still heavily r…
Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training
Ramon Sanabria, Wei-Ning Hsu, Alexei Baevski +1
Human speech data comprises a rich set of domain factors such as accent, syntactic and semantic variety, or acoustic environment. Previous work explores the effect of domain mismat…