1 citations · 5 across the 8 of their papers we have counts for
9 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…
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…
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…
A Novel Temporal Attentive-Pooling based Convolutional Recurrent Architecture for Acoustic Signal Enhancement
Tassadaq Hussain, Wei-Chien Wang, Mandar Gogate +5
In acoustic signal processing, the target signals usually carry semantic information, which is encoded in a hierarchal structure of short and long-term contexts. However, the backg…
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…
An Audio-Based Deep Learning Framework For BBC Television Programme Classification
Lam Pham, Chris Baume, Qiuqiang Kong +3
This paper proposes a deep learning framework for classification of BBC television programmes using audio. The audio is firstly transformed into spectrograms, which are fed into a…