16 citations · 21 across the 10 of their papers we have counts for
10 papers
Difference-Driven Gating: Adaptive Feature Fusion for U-Net Decoder
Kai Li, Xuechao Zou, Jiashen Fu +3
The U-Net style models have been widely used in many applications. A critical step in these models is to reconstruct the lower-level features using a top-down decoder. This reconst…
Efficient Audio-Visual Speech Separation with Discrete Lip Semantics and Multi-Scale Global-Local Attention
Kai Li, Kejun Gao, Xiaolin Hu
Audio-visual speech separation (AVSS) methods leverage visual cues to extract target speech and have demonstrated strong separation quality in noisy acoustic environments. However,…
A Fast and Lightweight Model for Causal Audio-Visual Speech Separation
Wendi Sang, Kai Li, Runxuan Yang +2
Audio-visual speech separation (AVSS) aims to extract a target speech signal from a mixed signal by leveraging both auditory and visual (lip movement) cues. However, most existing…
TDFNet: An Efficient Audio-Visual Speech Separation Model with Top-down Fusion
Samuel Pegg, Kai Li, Xiaolin Hu
Audio-visual speech separation has gained significant traction in recent years due to its potential applications in various fields such as speech recognition, diarization, scene an…
RTFS-Net: Recurrent Time-Frequency Modelling for Efficient Audio-Visual Speech Separation
Samuel Pegg, Kai Li, Xiaolin Hu
Audio-visual speech separation methods aim to integrate different modalities to generate high-quality separated speech, thereby enhancing the performance of downstream tasks such a…
IIANet: An Intra- and Inter-Modality Attention Network for Audio-Visual Speech Separation
Kai Li, Runxuan Yang, Fuchun Sun +1
Recent research has made significant progress in designing fusion modules for audio-visual speech separation. However, they predominantly focus on multi-modal fusion at a single te…
Audio-Visual Speech Separation in Noisy Environments with a Lightweight Iterative Model
Héctor Martel, Julius Richter, Kai Li +2
We propose Audio-Visual Lightweight ITerative model (AVLIT), an effective and lightweight neural network that uses Progressive Learning (PL) to perform audio-visual speech separati…
An Audio-Visual Speech Separation Model Inspired by Cortico-Thalamo-Cortical Circuits
Kai Li, Fenghua Xie, Hang Chen +2
Audio-visual approaches involving visual inputs have laid the foundation for recent progress in speech separation. However, the optimization of the concurrent usage of auditory and…
An efficient encoder-decoder architecture with top-down attention for speech separation
Kai Li, Runxuan Yang, Xiaolin Hu
Deep neural networks have shown excellent prospects in speech separation tasks. However, obtaining good results while keeping a low model complexity remains challenging in real-wor…
On the Use of Deep Mask Estimation Module for Neural Source Separation Systems
Kai Li, Xiaolin Hu, Yi Luo
Most of the recent neural source separation systems rely on a masking-based pipeline where a set of multiplicative masks are estimated from and applied to a signal representation o…