14 citations · 75 across the 18 of their papers we have counts for
18 papers
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…
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…
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…
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…
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…
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…
LMEC: Learnable Multiplicative Absolute Position Embedding Based Conformer for Speech Recognition
Yuguang Yang, Yu Pan, Jingjing Yin +1
This paper proposes a Learnable Multiplicative absolute position Embedding based Conformer (LMEC). It contains a kernelized linear attention (LA) module called LMLA to solve the ti…
Automatic Depth Optimization for Quantum Approximate Optimization Algorithm
Yu Pan, Yifan Tong, Yi Yang
Quantum Approximate Optimization Algorithm (QAOA) is a hybrid algorithm whose control parameters are classically optimized. In addition to the variational parameters, the right cho…
A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks
Yu Pan, Zeyong Su, Ao Liu +3
Tensorial Convolutional Neural Networks (TCNNs) have attracted much research attention for their power in reducing model parameters or enhancing the generalization ability. However…
Semantically Proportional Patchmix for Few-Shot Learning
Jingquan Wang, Jing Xu, Yu Pan +1
Few-shot learning aims to classify unseen classes with only a limited number of labeled data. Recent works have demonstrated that training models with a simple transfer learning st…
Graph Partner Neural Networks for Semi-Supervised Learning on Graphs
Langzhang Liang, Cuiyun Gao, Shiyi Chen +5
Graph Convolutional Networks (GCNs) are powerful for processing graph-structured data and have achieved state-of-the-art performance in several tasks such as node classification, l…
Fast query-by-example speech search using separable model
Yuguang Yang, Yu Pan, Xin Dong +1
Traditional Query-by-Example (QbE) speech search approaches usually use methods based on frame-level features, while state-of-the-art approaches tend to use models based on acousti…
Residual Tensor Train: A Quantum-inspired Approach for Learning Multiple Multilinear Correlations
Yiwei Chen, Yu Pan, Daoyi Dong
States of quantum many-body systems are defined in a high-dimensional Hilbert space, where rich and complex interactions among subsystems can be modelled. In machine learning, comp…
AFINet: Attentive Feature Integration Networks for Image Classification
Xinglin Pan, Jing Xu, Yu Pan +4
Convolutional Neural Networks (CNNs) have achieved tremendous success in a number of learning tasks including image classification. Recent advanced models in CNNs, such as ResNets,…
TedNet: A Pytorch Toolkit for Tensor Decomposition Networks
Yu Pan, Maolin Wang, Zenglin Xu
Tensor Decomposition Networks (TDNs) prevail for their inherent compact architectures. To give more researchers a flexible way to exploit TDNs, we present a Pytorch toolkit named T…
RegNet: Self-Regulated Network for Image Classification
Jing Xu, Yu Pan, Xinglin Pan +3
The ResNet and its variants have achieved remarkable successes in various computer vision tasks. Despite its success in making gradient flow through building blocks, the simple sho…
Heuristic Rank Selection with Progressively Searching Tensor Ring Network
Nannan Li, Yu Pan, Yaran Chen +3
Recently, Tensor Ring Networks (TRNs) have been applied in deep networks, achieving remarkable successes in compression ratio and accuracy. Although highly related to the performan…
Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition
Yu Pan, Jing Xu, Maolin Wang +4
Recurrent Neural Networks (RNNs) and their variants, such as Long-Short Term Memory (LSTM) networks, and Gated Recurrent Unit (GRU) networks, have achieved promising performance in…