255 citations · 780 across the 58 of their papers we have counts for
4 papers · 2 filters
On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement
Morten Kolbæk, Zheng-Hua Tan, Søren Holdt Jensen +1
Many deep learning-based speech enhancement algorithms are designed to minimize the mean-square error (MSE) in some transform domain between a predicted and a target speech signal.…
Keyword Spotting for Hearing Assistive Devices Robust to External Speakers
Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen
Keyword spotting (KWS) is experiencing an upswing due to the pervasiveness of small electronic devices that allow interaction with them via speech. Often, KWS systems are speaker-i…
rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method
Zheng-Hua Tan, Achintya kr. Sarkar, Najim Dehak
This paper presents an unsupervised segment-based method for robust voice activity detection (rVAD). The method consists of two passes of denoising followed by a voice activity det…
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…