4 papers
LLM-Guided Reinforcement Learning for Audio-Visual Speech Enhancement
Chih-Ning Chen, Jen-Cheng Hou, Hsin-Min Wang +3
In existing Audio-Visual Speech Enhancement (AVSE) methods, objectives such as Scale-Invariant Signal-to-Noise Ratio (SI-SNR) and Mean Squared Error (MSE) are widely used; however,…
Bridging The Multi-Modality Gaps of Audio, Visual and Linguistic for Speech Enhancement
Meng-Ping Lin, Jen-Cheng Hou, Chia-Wei Chen +4
Speech enhancement (SE) aims to improve the quality and intelligibility of speech in noisy environments. Recent studies have shown that incorporating visual cues in audio signal pr…
Towards Environmental Preference Based Speech Enhancement For Individualised Multi-Modal Hearing Aids
Jasper Kirton-Wingate, Shafique Ahmed, Adeel Hussain +6
Since the advent of Deep Learning (DL), Speech Enhancement (SE) models have performed well under a variety of noise conditions. However, such systems may still introduce sonic arte…
Deep Complex U-Net with Conformer for Audio-Visual Speech Enhancement
Shafique Ahmed, Chia-Wei Chen, Wenze Ren +7
Recent studies have increasingly acknowledged the advantages of incorporating visual data into speech enhancement (SE) systems. In this paper, we introduce a novel audio-visual SE…