45 citations · 69 across the 12 of their papers we have counts for
13 papers
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…
Audio-Visual Speech Enhancement in Noisy Environments via Emotion-Based Contextual Cues
Tassadaq Hussain, Kia Dashtipour, Yu Tsao +1
In real-world environments, background noise significantly degrades the intelligibility and clarity of human speech. Audio-visual speech enhancement (AVSE) attempts to restore spee…
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…
Leveraging Self-Supervised Audio-Visual Pretrained Models to Improve Vocoded Speech Intelligibility in Cochlear Implant Simulation
Richard Lee Lai, Jen-Cheng Hou, I-Chun Chern +6
Individuals with hearing impairments face challenges in their ability to comprehend speech, particularly in noisy environments. The aim of this study is to explore the effectivenes…
A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids
Abhijeet Bishnu, Ankit Gupta, Mandar Gogate +5
In this paper, we design a first of its kind transceiver (PHY layer) prototype for cloud-based audio-visual (AV) speech enhancement (SE) complying with high data rate and low laten…
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings
I-Chun Chern, Kuo-Hsuan Hung, Yi-Ting Chen +5
AV-HuBERT, a multi-modal self-supervised learning model, has been shown to be effective for categorical problems such as automatic speech recognition and lip-reading. This suggests…
Canonical Cortical Graph Neural Networks and its Application for Speech Enhancement in Audio-Visual Hearing Aids
Leandro A. Passos, João Paulo Papa, Amir Hussain +1
Despite the recent success of machine learning algorithms, most models face drawbacks when considering more complex tasks requiring interaction between different sources, such as m…
A Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning for Hearing-Assistive Technologies
Tassadaq Hussain, Muhammad Diyan, Mandar Gogate +4
Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are generally trained to minimise the distance between clean and enhanced sp…
A Novel Speech Intelligibility Enhancement Model based on CanonicalCorrelation and Deep Learning
Tassadaq Hussain, Muhammad Diyan, Mandar Gogate +4
Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are often trained to minimise the feature distance between noise-free speech…
A Novel Chaos-based Light-weight Image Encryption Scheme for Multi-modal Hearing Aids
Awais Aziz Shah, Ahsan Adeel, Jawad Ahmad +8
Multimodal hearing aids (HAs) aim to deliver more intelligible audio in noisy environments by contextually sensing and processing data in the form of not only audio but also visual…
Multimodal Audio-Visual Information Fusion using Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement
Leandro Aparecido Passos, João Paulo Papa, Javier Del Ser +2
This paper proposes a novel multimodal self-supervised architecture for energy-efficient audio-visual (AV) speech enhancement that integrates Graph Neural Networks with canonical c…
Towards Robust Real-time Audio-Visual Speech Enhancement
Mandar Gogate, Kia Dashtipour, Amir Hussain
The human brain contextually exploits heterogeneous sensory information to efficiently perform cognitive tasks including vision and hearing. For example, during the cocktail party…
Towards Intelligibility-Oriented Audio-Visual Speech Enhancement
Tassadaq Hussain, Mandar Gogate, Kia Dashtipour +1
Existing deep learning (DL) based speech enhancement approaches are generally optimised to minimise the distance between clean and enhanced speech features. These often result in i…