18 citations · 45 across the 6 of their papers we have counts for
6 papers
Deep Speaker Vector Normalization with Maximum Gaussianality Training
Yunqi Cai, Lantian Li, Dong Wang +1
Deep speaker embedding represents the state-of-the-art technique for speaker recognition. A key problem with this approach is that the resulting deep speaker vectors tend to be irr…
Deep Normalization for Speaker Vectors
Yunqi Cai, Lantian Li, Dong Wang +1
Deep speaker embedding has demonstrated state-of-the-art performance in speaker recognition tasks. However, one potential issue with this approach is that the speaker vectors deriv…
Memory-augmented Neural Machine Translation
Yang Feng, Shiyue Zhang, Andi Zhang +2
Neural machine translation (NMT) has achieved notable success in recent times, however it is also widely recognized that this approach has limitations with handling infrequent word…
Flexible and Creative Chinese Poetry Generation Using Neural Memory
Jiyuan Zhang, Yang Feng, Dong Wang +4
It has been shown that Chinese poems can be successfully generated by sequence-to-sequence neural models, particularly with the attention mechanism. A potential problem of this app…
Phonetic Temporal Neural Model for Language Identification
Zhiyuan Tang, Dong Wang, Yixiang Chen +2
Deep neural models, particularly the LSTM-RNN model, have shown great potential for language identification (LID). However, the use of phonetic information has been largely overloo…
Probabilistic Belief Embedding for Knowledge Base Completion
Miao Fan, Qiang Zhou, Andrew Abel +2
This paper contributes a novel embedding model which measures the probability of each belief in a large-scale knowledge repository via simultaneously learn…