HiLAM-state discriminative multi-task deep neural network in dynamic time warping framework for text-dependent speaker verification
Abstract
This paper builds on a multi-task Deep Neural Network (DNN), which provides an utterance-level feature representation called j-vector, to implement a Text-dependent Speaker Verification (TDSV) system. This technique exploits the speaker idiosyncrasies associated with individual pass-phrases. However, speaker information is known to be characteristic of more specific speech units and, thus, it is likely that important speaker identity traits...
Paper Details
Title
HiLAM-state discriminative multi-task deep neural network in dynamic time warping framework for text-dependent speaker verification
Published Date
Aug 1, 2020
Journal
Volume
121
Pages
29 - 43
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