46 citations · 177 across the 28 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.SD2019★ 32 cited
Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification
Achintya kr. Sarkar, Zheng-Hua Tan, Hao Tang +2
There are a number of studies about extraction of bottleneck (BN) features from deep neural networks (DNNs)trained to discriminate speakers, pass-phrases and triphone states for im…
eess.AS2019
VoiceID Loss: Speech Enhancement for Speaker Verification
Suwon Shon, Hao Tang, James Glass
In this paper, we propose VoiceID loss, a novel loss function for training a speech enhancement model to improve the robustness of speaker verification. In contrast to the commonly…
cs.CL2019★ 46 cited
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…