All Outputs (44)

Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN (2024)
Journal Article
Gogate, M., Dashtipour, K., & Hussain, A. (in press). Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN. IEEE Transactions on Artificial Intelligence, https://doi.org/10.1109/tai.2024.3366141

The human auditory cortex contextually integrates audio-visual (AV) cues to better understand speech in a cocktail party situation. Recent studies have shown that AV speech enhancement (SE) models can significantly improve speech quality and intellig... Read More about Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN.

A hybrid dependency-based approach for Urdu sentiment analysis (2023)
Journal Article
Sehar, U., Kanwal, S., Allheeib, N. I., Almari, S., Khan, F., Dashtipur, K., …Khashan, O. A. (2023). A hybrid dependency-based approach for Urdu sentiment analysis. Scientific Reports, 13, Article 22075. https://doi.org/10.1038/s41598-023-48817-8

In the digital age, social media has emerged as a significant platform, generating a vast amount of raw data daily. This data reflects the opinions of individuals from diverse backgrounds, races, cultures, and age groups, spanning a wide range of top... Read More about A hybrid dependency-based approach for Urdu sentiment analysis.

Formulations and Algorithms to Find Maximal and Maximum Independent Sets of Graphs (2023)
Conference Proceeding
Heal, M., Dashtipour, K., & Gogate, M. (2023). Formulations and Algorithms to Find Maximal and Maximum Independent Sets of Graphs. In Proceedings, 2022 International Conference on Computational Science and Computational Intelligence, CSCI 2022. https://doi.org/10.1109/csci58124.2022.00097

We propose four algorithms to find maximal and maximum independent sets of graphs. Two of the algorithms are non-polynomial in time, mainly binary programming and non-convex multi-variable polynomial programming algorithms. Two other algorithms run i... Read More about Formulations and Algorithms to Find Maximal and Maximum Independent Sets of Graphs.

Towards Pose-Invariant Audio-Visual Speech Enhancement in the Wild for Next-Generation Multi-Modal Hearing Aids (2023)
Conference Proceeding
Gogate, M., Dashtipour, K., & Hussain, A. (2023). Towards Pose-Invariant Audio-Visual Speech Enhancement in the Wild for Next-Generation Multi-Modal Hearing Aids. In 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW). https://doi.org/10.1109/icasspw59220.2023.10192961

Classical audio-visual (AV) speech enhancement (SE) and separation methods have been successful at operating under constrained environments; however, the speech quality and intelligibility improvement is significantly reduced in unconstrained real-wo... Read More about Towards Pose-Invariant Audio-Visual Speech Enhancement in the Wild for Next-Generation Multi-Modal Hearing Aids.

Sentiment Analysis Meets Explainable Artificial Intelligence: A Survey on Explainable Sentiment Analysis (2023)
Journal Article
Diwali, A., Saeedi, K., Dashtipour, K., Gogate, M., Cambria, E., & Hussain, A. (in press). Sentiment Analysis Meets Explainable Artificial Intelligence: A Survey on Explainable Sentiment Analysis. IEEE Transactions on Affective Computing, https://doi.org/10.1109/taffc.2023.3296373

Sentiment analysis can be used to derive knowledge that is connected to emotions and opinions from textual data generated by people. As computer power has grown, and the availability of benchmark datasets has increased, deep learning models based on... Read More about Sentiment Analysis Meets Explainable Artificial Intelligence: A Survey on Explainable Sentiment Analysis.

Arabic Sentiment Analysis Based on Word Embeddings and Deep Learning (2023)
Journal Article
Elhassan, N., Varone, G., Ahmed, R., Gogate, M., Dashtipour, K., Almoamari, H., …Hussain, A. (2023). Arabic Sentiment Analysis Based on Word Embeddings and Deep Learning. Computers, 12(6), Article 126. https://doi.org/10.3390/computers12060126

Social media networks have grown exponentially over the last two decades, providing the opportunity for users of the internet to communicate and exchange ideas on a variety of topics. The outcome is that opinion mining plays a crucial role in analyzi... Read More about Arabic Sentiment Analysis Based on Word Embeddings and Deep Learning.

Towards Individualised Speech Enhancement: An SNR Preference Learning System for Multi-Modal Hearing Aids (2023)
Conference Proceeding
Kirton-Wingate, J., Ahmed, S., Gogate, M., Tsao, Y., & Hussain, A. (2023). Towards Individualised Speech Enhancement: An SNR Preference Learning System for Multi-Modal Hearing Aids. In K. Dashtipour (Ed.), Proceedings of the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW). https://doi.org/10.1109/icasspw59220.2023.10193122

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 artefacts, sound unnatural, and restrict the ability for a user to hear am... Read More about Towards Individualised Speech Enhancement: An SNR Preference Learning System for Multi-Modal Hearing Aids.

Live Demonstration: Real-time Multi-modal Hearing Assistive Technology Prototype (2023)
Conference Proceeding
Gogate, M., Hussain, A., Dashtipour, K., & Hussain, A. (2023). Live Demonstration: Real-time Multi-modal Hearing Assistive Technology Prototype. In IEEE ISCAS 2023 Symposium Proceedings. https://doi.org/10.1109/iscas46773.2023.10182070

Hearing loss affects at least 1.5 billion people globally. The WHO estimates 83% of people who could benefit from hearing aids do not use them. Barriers to HA uptake are multifaceted but include ineffectiveness of current HA technology in noisy envir... Read More about Live Demonstration: Real-time Multi-modal Hearing Assistive Technology Prototype.

Live Demonstration: Cloud-based Audio-Visual Speech Enhancement in Multimodal Hearing-aids (2023)
Conference Proceeding
Bishnu, A., Gupta, A., Gogate, M., Dashtipour, K., Arslan, T., Adeel, A., …Ratnarajah, T. (2023). Live Demonstration: Cloud-based Audio-Visual Speech Enhancement in Multimodal Hearing-aids. In IEEE ISCAS 2023 Symposium Proceedings. https://doi.org/10.1109/iscas46773.2023.10182060

Hearing loss is among the most serious public health problems, affecting as much as 20% of the worldwide population. Even cutting-edge multi-channel audio-only speech enhancement (SE) algorithms used in modern hearing aids face significant hurdles si... Read More about Live Demonstration: Cloud-based Audio-Visual Speech Enhancement in Multimodal Hearing-aids.

The P vs. NP Problem and Attempts to Settle It via Perfect Graphs State-of-the-Art Approach (2023)
Conference Proceeding
Heal, M., Dashtipour, K., & Gogate, M. (2023). The P vs. NP Problem and Attempts to Settle It via Perfect Graphs State-of-the-Art Approach. In Advances in Information and Communication: Proceedings of the 2023 Future of Information and Communication Conference (FICC), Volume 2 (328-340). https://doi.org/10.1007/978-3-031-28073-3_23

The P vs. NP problem is a major problem in computer science. It is perhaps the most celebrated outstanding problem in that domain. Its solution would have a tremendous impact on different fields such as mathematics, cryptography, algorithm research,... Read More about The P vs. NP Problem and Attempts to Settle It via Perfect Graphs State-of-the-Art Approach.

Interactive Effect of Learning Rate and Batch Size to Implement Transfer Learning for Brain Tumor Classification (2023)
Journal Article
Usmani, I. A., Qadri, M. T., Zia, R., Alrayes, F. S., Saidani, O., & Dashtipour, K. (2023). Interactive Effect of Learning Rate and Batch Size to Implement Transfer Learning for Brain Tumor Classification. Electronics, 12(4), Article 964. https://doi.org/10.3390/electronics12040964

For classifying brain tumors with small datasets, the knowledge-based transfer learning (KBTL) approach has performed very well in attaining an optimized classification model. However, its successful implementation is typically affected by different... Read More about Interactive Effect of Learning Rate and Batch Size to Implement Transfer Learning for Brain Tumor Classification.

A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting (2023)
Journal Article
Varone, G., Ieracitano, C., Çiftçioğlu, A. Ö., Hussain, T., Gogate, M., Dashtipour, K., …Hussain, A. (2023). A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting. Entropy, 25(2), Article 253. https://doi.org/10.3390/e25020253

The development of reinforced polymer composite materials has had a significant influence on the challenging problem of shielding against high-energy photons, particularly X-rays and γ-rays in industrial and healthcare facilities. Heavy materials’ sh... Read More about A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting.

AVSE Challenge: Audio-Visual Speech Enhancement Challenge (2023)
Conference Proceeding
Aldana Blanco, A. L., Valentini-Botinhao, C., Klejch, O., Gogate, M., Dashtipour, K., Hussain, A., & Bell, P. (2023). AVSE Challenge: Audio-Visual Speech Enhancement Challenge. In 2022 IEEE Spoken Language Technology Workshop (SLT) (465-471). https://doi.org/10.1109/slt54892.2023.10023284

Audio-visual speech enhancement is the task of improving the quality of a speech signal when video of the speaker is available. It opens-up the opportunity of improving speech intelligibility in adverse listening scenarios that are currently too chal... Read More about AVSE Challenge: Audio-Visual Speech Enhancement Challenge.

A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids (2022)
Conference Proceeding
Bishnu, A., Gupta, A., Gogate, M., Dashtipour, K., Adeel, A., Hussain, A., …Ratnarajah, T. (2022). A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids. In 2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom). https://doi.org/10.1109/healthcom54947.2022.9982772

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 latency requirements of future multimodal hearing assistive technology. The... Read More about A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids.

Towards real-time privacy-preserving audio-visual speech enhancement (2022)
Presentation / Conference
Gogate, M., Dashtipour, K., & Hussain, A. (2022, September). Towards real-time privacy-preserving audio-visual speech enhancement. Paper presented at 2nd Symposium on Security and Privacy in Speech Communication, Incheon, Korea

Human auditory cortex in everyday noisy situations is known to exploit aural and visual cues that are contextually combined by the brain’s multi-level integration strategies to selectively suppress the background noise and focus on the target speaker... Read More about Towards real-time privacy-preserving audio-visual speech enhancement.

A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning (2022)
Conference Proceeding
Hussain, T., Diyan, M., Gogate, M., Dashtipour, K., Adeel, A., Tsao, Y., & Hussain, A. (2022). A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). https://doi.org/10.1109/embc48229.2022.9871113

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 and enhanced speech signals. Despite improving the speech quality, su... Read More about A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning.

Arabic sentiment analysis using dependency-based rules and deep neural networks (2022)
Journal Article
Diwali, A., Dashtipour, K., Saeedi, K., Gogate, M., Cambria, E., & Hussain, A. (2022). Arabic sentiment analysis using dependency-based rules and deep neural networks. Applied Soft Computing, 127, Article 109377. https://doi.org/10.1016/j.asoc.2022.109377

With the growth of social platforms in recent years and the rapid increase in the means of communication through these platforms, a significant amount of textual data is available that contains an abundance of individuals’ opinions. Sentiment analysi... Read More about Arabic sentiment analysis using dependency-based rules and deep neural networks.

Artificial intelligence-enabled social media analysis for pharmacovigilance of COVID-19 vaccinations in the United Kingdom: Observational Study (2022)
Journal Article
Hussain, Z., Sheikh, Z., Tahir, A., Dashtipour, K., Gogate, M., Sheikh, A., & Hussain, A. (2022). Artificial intelligence-enabled social media analysis for pharmacovigilance of COVID-19 vaccinations in the United Kingdom: Observational Study. JMIR Public Health and Surveillance, 8(5), Article e32543. https://doi.org/10.2196/32543

Background: The roll-out of vaccines for SARS-CoV-2 in the United Kingdom, started in December 2020. Uptake has been high, and there has been a subsequent reduction in infections, hospitalisations and deaths in vaccinated individuals. However, vacci... Read More about Artificial intelligence-enabled social media analysis for pharmacovigilance of COVID-19 vaccinations in the United Kingdom: Observational Study.

A Novel Temporal Attentive-Pooling based Convolutional Recurrent Architecture for Acoustic Signal Enhancement (2022)
Journal Article
Hussain, T., Wang, W., Gogate, M., Dashtipour, K., Tsao, Y., Lu, X., …Hussain, A. (2022). A Novel Temporal Attentive-Pooling based Convolutional Recurrent Architecture for Acoustic Signal Enhancement. IEEE Transactions on Artificial Intelligence, 3(5), 833-842. https://doi.org/10.1109/TAI.2022.3169995

Removing background noise from acoustic observations to obtain clean signals is an important research topic regarding numerous real acoustic applications. Owing to their strong model capacity in function mapping, deep neural network-based algorithms... Read More about A Novel Temporal Attentive-Pooling based Convolutional Recurrent Architecture for Acoustic Signal Enhancement.

Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform (2022)
Journal Article
Abd, M. H., Al-Suhail, G. A., Tahir, F. R., Ali Ali, A. M., Abbood, H. A., Dashtipour, K., …Ahmad, J. (2022). Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform. Remote Sensing, 14(9), Article 1984. https://doi.org/10.3390/rs14091984

There is no doubt that chaotic systems are still attractive issues in various radar applications and communication systems. In this paper, we present a new 0.3 GHz mono-static microwave chaotic radar. It includes a chaotic system based on a time-dela... Read More about Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform.