activity
20162022
most citedLearning Deep Representations of Medical Images using Siamese CNNs with Application to Content-Based Image Retrieval

62 citations · 305 across the 15 of their papers we have counts for

collaborators

23 papers

cs.CL20225 cited

Speech-to-Speech Translation For A Real-world Unwritten Language

Peng-Jen Chen, Kevin Tran, Yilin Yang +13

We study speech-to-speech translation (S2ST) that translates speech from one language into another language and focuses on building systems to support languages without standard te…

cs.CL202150 cited

SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training

Ankur Bapna, Yu-an Chung, Nan Wu +7

Unsupervised pre-training is now the predominant approach for both text and speech understanding. Self-attention models pre-trained on large amounts of unannotated data have been h…

cs.LG202115 cited

W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training

Yu-An Chung, Yu Zhang, Wei Han +4

Motivated by the success of masked language modeling~(MLM) in pre-training natural language processing models, we propose w2v-BERT that explores MLM for self-supervised speech repr…

cs.SD2021

AST: Audio Spectrogram Transformer

Yuan Gong, Yu-An Chung, James Glass

In the past decade, convolutional neural networks (CNNs) have been widely adopted as the main building block for end-to-end audio classification models, which aim to learn a direct…

cs.CL2020

Non-Autoregressive Predictive Coding for Learning Speech Representations from Local Dependencies

Alexander H. Liu, Yu-An Chung, James Glass

Self-supervised speech representations have been shown to be effective in a variety of speech applications. However, existing representation learning methods generally rely on the…

eess.AS2020

Similarity Analysis of Self-Supervised Speech Representations

Yu-An Chung, Yonatan Belinkov, James Glass

Self-supervised speech representation learning has recently been a prosperous research topic. Many algorithms have been proposed for learning useful representations from large-scal…