99 citations · 115 across the 8 of their papers we have counts for
8 papers
EEG-Derived Voice Signature for Attended Speaker Detection
Hongxu Zhu, Siqi Cai, Yidi Jiang +2
\textit{Objective:} Conventional EEG-based auditory attention detection (AAD) is achieved by comparing the time-varying speech stimuli and the elicited EEG signals. However, in ord…
Ripple sparse self-attention for monaural speech enhancement
Qiquan Zhang, Hongxu Zhu, Qi Song +3
The use of Transformer represents a recent success in speech enhancement. However, as its core component, self-attention suffers from quadratic complexity, which is computationally…
PoE: a Panel of Experts for Generalized Automatic Dialogue Assessment
Chen Zhang, Luis Fernando D'Haro, Qiquan Zhang +2
Chatbots are expected to be knowledgeable across multiple domains, e.g. for daily chit-chat, exchange of information, and grounding in emotional situations. To effectively measure…
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension
Peng Gao, Feng Gao, Jian-Cheng Ni +2
Drug-drug interaction prediction is a crucial issue in molecular biology. Traditional methods of observing drug-drug interactions through medical experiments require significant re…
FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation
Chen Zhang, Luis Fernando D'Haro, Qiquan Zhang +2
Recent model-based reference-free metrics for open-domain dialogue evaluation exhibit promising correlations with human judgment. However, they either perform turn-level evaluation…
Time-Frequency Attention for Monaural Speech Enhancement
Qiquan Zhang, Qi Song, Zhaoheng Ni +2
Most studies on speech enhancement generally don't consider the energy distribution of speech in time-frequency (T-F) representation, which is important for accurate prediction of…
Monaural Speech Enhancement Using a Multi-Branch Temporal Convolutional Network
Qiquan Zhang, Aaron Nicolson, Mingjiang Wang +2
Deep learning has achieved substantial improvement on single-channel speech enhancement tasks. However, the performance of multi-layer perceptions (MLPs)-based methods is limited b…
Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Peng Gao, Qiquan Zhang, Fei Wang +3
Although numerous recent tracking approaches have made tremendous advances in the last decade, achieving high-performance visual tracking remains a challenge. In this paper, we pro…