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20182023
most citedTensor Networks Meet Neural Networks: A Survey and Future Perspectives

14 citations · 75 across the 18 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

eess.AS2023★ 1 cited

PromptVC: Flexible Stylistic Voice Conversion in Latent Space Driven by Natural Language Prompts

Jixun Yao, Yuguang Yang, Yi Lei +7

Style voice conversion aims to transform the style of source speech to a desired style according to real-world application demands. However, the current style voice conversion appr…

cs.SD2023★ 3 cited

MSAC: Multiple Speech Attribute Control Method for Reliable Speech Emotion Recognition

Yu Pan, Yuguang Yang, Yuheng Huang +6

Despite notable progress, speech emotion recognition (SER) remains challenging due to the intricate and ambiguous nature of speech emotion, particularly in wild world. While curren…

cs.CL2023

GEmo-CLAP: Gender-Attribute-Enhanced Contrastive Language-Audio Pretraining for Accurate Speech Emotion Recognition

Yu Pan, Yanni Hu, Yuguang Yang +5

Contrastive cross-modality pretraining has recently exhibited impressive success in diverse fields, whereas there is limited research on their merits in speech emotion recognition…

cs.AI2023

Tensorized Hypergraph Neural Networks

Maolin Wang, Yaoming Zhen, Yu Pan +5

Hypergraph neural networks (HGNN) have recently become attractive and received significant attention due to their excellent performance in various domains. However, most existing H…

eess.AS2023

HYBRIDFORMER: improving SqueezeFormer with hybrid attention and NSR mechanism

Yuguang Yang, Yu Pan, Jingjing Yin +3

SqueezeFormer has recently shown impressive performance in automatic speech recognition (ASR). However, its inference speed suffers from the quadratic complexity of softmax-attenti…

cs.LG2023★ 14 cited

Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Maolin Wang, Yu Pan, Zenglin Xu +4

Tensor networks (TNs) and neural networks (NNs) are two fundamental data modeling approaches. TNs were introduced to solve the curse of dimensionality in large-scale tensors by con…