432 citations · 832 across the 20 of their papers we have counts for
22 papers
Audio-Visual Feature Synchronization for Robust Speech Enhancement in Hearing Aids
Nasir Saleem, Mandar Gogate, Kia Dashtipour +5
Audio-visual feature synchronization for real-time speech enhancement in hearing aids represents a progressive approach to improving speech intelligibility and user experience, par…
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…
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…
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 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…
A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis
Kia Dashtipour, Mandar Gogate, Erik Cambria +1
Most recent works on sentiment analysis have exploited the text modality. However, millions of hours of video recordings posted on social media platforms everyday hold vital unstru…
An Experimental Analysis of Attack Classification Using Machine Learning in IoT Networks
Andrew Churcher, Rehmat Ullah, Jawad Ahmad +6
In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT…
AV Speech Enhancement Challenge using a Real Noisy Corpus
Mandar Gogate, Ahsan Adeel, Kia Dashtipour +2
This paper presents, a first of its kind, audio-visual (AV) speech enhacement challenge in real-noisy settings. A detailed description of the AV challenge, a novel real noisy AV co…
A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks
Kia Dashtipour, Mandar Gogate, Jingpeng Li +3
Social media hold valuable, vast and unstructured information on public opinion that can be utilized to improve products and services. The automatic analysis of such data, however,…
CochleaNet: A Robust Language-independent Audio-Visual Model for Speech Enhancement
Mandar Gogate, Kia Dashtipour, Ahsan Adeel +1
Noisy situations cause huge problems for suffers of hearing loss as hearing aids often make the signal more audible but do not always restore the intelligibility. In noisy settings…
A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management
Ahsan Adeel, Mandar Gogate, Saadullah Farooq +4
Extreme events and disasters resulting from climate change or other ecological factors are difficult to predict and manage. Current limitations of state-of-the-art approaches to di…
Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments
Ahsan Adeel, Mandar Gogate, Amir Hussain
Human speech processing is inherently multimodal, where visual cues (lip movements) help to better understand the speech in noise. Lip-reading driven speech enhancement significant…
Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection
Cosimo Ieracitano, Ahsan Adeel, Mandar Gogate +5
Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology systems. The extent of damage an individual hacker can carry…
Exploiting Deep Learning for Persian Sentiment Analysis
Kia Dashtipour, Mandar Gogate, Ahsan Adeel +3
The rise of social media is enabling people to freely express their opinions about products and services. The aim of sentiment analysis is to automatically determine subject's sent…
DNN driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation
Mandar Gogate, Ahsan Adeel, Ricard Marxer +2
Human auditory cortex excels at selectively suppressing background noise to focus on a target speaker. The process of selective attention in the brain is known to contextually expl…
Lip-Reading Driven Deep Learning Approach for Speech Enhancement
Ahsan Adeel, Mandar Gogate, Amir Hussain +1
This paper proposes a novel lip-reading driven deep learning framework for speech enhancement. The proposed approach leverages the complementary strengths of both deep learning and…