no code implementations • 11 Oct 2021 • Shujun Liu, Hai Zhu, Kun Wang, Huajun Wang
For the phoneme encoder, based on the analysis that same phonemes corresponding to varying pitches can produce similar pronunciations, this encoder is followed by an adversarially trained pitch classifier to enforce the identical phonemes with different pitches mapping into the same phoneme feature space.
no code implementations • 16 Dec 2019 • Huajun Wang, Yuan-Hai Shao, Shenglong Zhou, Ce Zhang, Naihua Xiu
To distinguish all of them, in this paper, we introduce a new model equipped with an $L_{0/1}$ soft-margin loss (dubbed as $L_{0/1}$-SVM) which well captures the nature of the binary classification.
no code implementations • 22 Oct 2019 • Chun-Na Li, Yuan-Hai Shao, Huajun Wang, Yu-Ting Zhao, Ling-Wei Huang, Naihua Xiu, Nai-Yang Deng
The other type constructs all the hyperplanes simultaneously, and it solves one big optimization problem with the ascertained loss of each sample.