241 citations · 1.2k across the 60 of their papers we have counts for
4 papers · 1 filter
Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech
David Harwath, Wei-Ning Hsu, James Glass
In this paper, we present a method for learning discrete linguistic units by incorporating vector quantization layers into neural models of visually grounded speech. We show that o…
Transfer Learning from Audio-Visual Grounding to Speech Recognition
Wei-Ning Hsu, David Harwath, James Glass
Transfer learning aims to reduce the amount of data required to excel at a new task by re-using the knowledge acquired from learning other related tasks. This paper proposes a nove…
An Unsupervised Autoregressive Model for Speech Representation Learning
Yu-An Chung, Wei-Ning Hsu, Hao Tang +1
This paper proposes a novel unsupervised autoregressive neural model for learning generic speech representations. In contrast to other speech representation learning methods that a…
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Jonathan Shen, Patrick Nguyen, Yonghui Wu +88
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…