1 citations · 1 across the 2 of their papers we have counts for
4 papers
DBMIF: a deep balanced multimodal iterative fusion framework for air- and bone-conduction speech enhancement
Yilei Wu, Changyan Zheng, Xingyu Zhang +5
The performance of conventional speech enhancement systems degrades sharply in extremely low signal-to-noise ratio (SNR) environments where air-conduction (AC) microphones are over…
Purification Before Fusion: Toward Mask-Free Speech Enhancement for Robust Audio-Visual Speech Recognition
Linzhi Wu, Xingyu Zhang, Hao Yuan +5
Audio-visual speech recognition (AVSR) typically improves recognition accuracy in noisy environments by integrating noise-immune visual cues with audio signals. Nevertheless, high-…
AVE Speech: A Comprehensive Multi-Modal Dataset for Speech Recognition Integrating Audio, Visual, and Electromyographic Signals
Dongliang Zhou, Yakun Zhang, Jinghan Wu +3
The global aging population faces considerable challenges, particularly in communication, due to the prevalence of hearing and speech impairments. To address these, we introduce th…
Landmark-Guided Cross-Speaker Lip Reading with Mutual Information Regularization
Linzhi Wu, Xingyu Zhang, Yakun Zhang +5
Lip reading, the process of interpreting silent speech from visual lip movements, has gained rising attention for its wide range of realistic applications. Deep learning approaches…