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20152022
most citedConstructing IGA-suitable planar parameterization from complex CAD boundary by domain partition and global/local optimization

112 citations · 276 across the 21 of their papers we have counts for

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6 papers · 1 filter

eess.AS20193 cited

Utterance-level end-to-end language identification using attention-based CNN-BLSTM

Weicheng Cai, Danwei Cai, Shen Huang +1

In this paper, we present an end-to-end language identification framework, the attention-based Convolutional Neural Network-Bidirectional Long-short Term Memory (CNN-BLSTM). The mo…

eess.AS2018

End-to-end Language Identification using NetFV and NetVLAD

Jinkun Chen, Weicheng Cai, Danwei Cai +3

In this paper, we apply the NetFV and NetVLAD layers for the end-to-end language identification task. NetFV and NetVLAD layers are the differentiable implementations of the standar…

eess.AS2018

Analysis of Length Normalization in End-to-End Speaker Verification System

Weicheng Cai, Jinkun Chen, Ming Li

The classical i-vectors and the latest end-to-end deep speaker embeddings are the two representative categories of utterance-level representations in automatic speaker verification…

eess.AS2018

Exploring the Encoding Layer and Loss Function in End-to-End Speaker and Language Recognition System

Weicheng Cai, Jinkun Chen, Ming Li

In this paper, we explore the encoding/pooling layer and loss function in the end-to-end speaker and language recognition system. First, a unified and interpretable end-to-end syst…

eess.AS2018

A Novel Learnable Dictionary Encoding Layer for End-to-End Language Identification

Weicheng Cai, Zexin Cai, Xiang Zhang +2

A novel learnable dictionary encoding layer is proposed in this paper for end-to-end language identification. It is inline with the conventional GMM i-vector approach both theoreti…

eess.AS2018

Insights into End-to-End Learning Scheme for Language Identification

Weicheng Cai, Zexin Cai, Wenbo Liu +2

A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically.…