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DF-ResNet: Boosting Speaker Verification performance with Depth-First Design 23

DF-ResNet: Boosting Speaker Verification Performance with De...

引用

Interspeech Conference

作者： Liu, Bei Chen, Zhengyang Wang, Shuai Wang, Haoyu Han, Bing Qian, Yanmin Shanghai Jiao Tong Univ X LANCE Lab MoE Key Lab Artificial Intelligence AI InstDept Comp Sci & Engn Shanghai Peoples R China

Embeddings extracted by deep neural networks have become the state-of-the-art utterance representation in speaker verification (SV). Despite the various network architectures that have been investigated in previous works, how to design and scale up networks to achieve a better trade-off on performance and complexity in a principled manner has been rarely discussed in the SV field. In this paper, we first systematically study model scaling from the perspective of the depth and width of networks and empirically discover that depth is more important than the width of networks for speaker verification task. Based on this observation, we design a new backbone constructed entirely from standard convolutional network modules by significantly increasing the number of layers while maintaining the network complexity following the depth-first rule and scale it up to obtain a family of much deeper models dubbed DF-ResNets. Comprehensive comparisons with other state-of-the-art systems on the Voxceleb dataset demonstrate that DF-ResNets achieve a much better trade-off than previous SV systems in terms of performance and complexity.

关键词： speaker verification model scaling performance and complexity

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An Improved Radius Adaptive K-Best Algorithm For MIMO System 2

An Improved Radius Adaptive K-Best Algorithm For MIMO System

引用

2nd IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Fang, Hanlin Ge, Lijia Zhu, Guoqing Chongqing Commun Inst Chongqing Key Lab Emergency Commun Chongqing Peoples R China

ISBN: (纸本)9781479920303

The K-Best algorithm can achieve high BER performance with a large K value, but the complexity is very high. The RAKB algorithm reduces the complexity and gets similar BER performance compares to the K-Best algorithm. However, with the antennas increase, the BER performance improvement of the RAKB algorithm is not obvious. This paper presents an improved algorithm which is based on the RAKB algorithm. Unlike the invariant K value used in the K-Best algorithm and the RAKB algorithm, we set a variable K value and bring in the SQRD method in the proposed algorithm. Simulation results show that with the number of antennas increase, the proposed algorithm has a noticeable BER performance improvement compares to the RAKB algorithm. Meanwhile, it may also reduce the complexity in terms of the visited nodes.

关键词： MIMO detection algorithm performance and complexity

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An Improved Radius Adaptive K-Best Algorithm For MIMO System

An Improved Radius Adaptive K-Best Algorithm For MIMO System

引用

2014 IEEE International Conference on Progress in Informatics and Computing

作者： Hanlin Fang Lijia Ge Guoqing Zhu Chongqing Key Laboratory of Emergency Communication Chongqing Communication Institute

The K-Best algorithm can achieve high BE performance with a large K value, but the complexity is very hig The RAKB algorithm reduces the complexity and gets simila BER performance compares tothe K-Best algorithm. Howeve with the antennas increase, the BER performance improveme of the RAKB algorithm is not obvious. This paper presents a improved algorithm which is based on the RAKB algorithm Unlike the invariant K value used in the K-Best algorithm an the RAKB algorithm, we set a variable K value and bring in th SQRD method in the proposed algorithm. Simulation resul show that with the number of antennas increase, the propose algorithm has a noticeable BER performance improveme compares tothe RAKB algorithm. Meanwhile, it may alsoredu the complexity in terms of the visited nodes.

关键词： MIMO detection algorithm performance and complexity

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