1 citations · 1 across the 4 of their papers we have counts for
5 papers
Property Neurons in Self-Supervised Speech Transformers
Tzu-Quan Lin, Guan-Ting Lin, Hung-yi Lee +1
There have been many studies on analyzing self-supervised speech Transformers, in particular, with layer-wise analysis. It is, however, desirable to have an approach that can pinpo…
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…
On the Utility of Self-supervised Models for Prosody-related Tasks
Guan-Ting Lin, Chi-Luen Feng, Wei-Ping Huang +5
Self-Supervised Learning (SSL) from speech data has produced models that have achieved remarkable performance in many tasks, and that are known to implicitly represent many aspects…
Context-gloss Augmentation for Improving Word Sense Disambiguation
Guan-Ting Lin, Manuel Giambi
The goal of Word Sense Disambiguation (WSD) is to identify the sense of a polysemous word in a specific context. Deep-learning techniques using BERT have achieved very promising re…
SUPERB: Speech processing Universal PERformance Benchmark
Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang +17
Self-supervised learning (SSL) has proven vital for advancing research in natural language processing (NLP) and computer vision (CV). The paradigm pretrains a shared model on large…