Publications

Gabor-based audiovisual fusion for Mandarin Chinese speech recognition

Xu Yan, Wang Hongce, Dong Zhongping, Li Yuexuan, Abel Andrew

2022 30th European Signal Processing Conference (EUSIPCO) 30th European Signal Processing Conference, EUSIPCO 2022 2022 30th European Signal Processing Conference (EUSIPCO), pp. 603-607 (2022)

https://doi.org/10.23919/eusipco55093.2022.9909634

Cognitive-load-aware multimodal video segmentation for adaptive consumer media systems

De Silva Waruna, Dong Feng, Abel Andrew, Fernando Anil

2026 IEEE International Conference on Consumer Electronics (ICCE) 44th IEEE International Conference on Consumer Electronics 2026 IEEE International Conference on Consumer Electronics (ICCE), pp. 1-6 (2026)

https://doi.org/10.1109/icce67443.2026.11449659

TranscribeSight : redefining ASR evaluation for Industry 4.0 knowledge capture

Alsayegh Ali, Ul Ain Noor, Abel Andrew, Jia Laibing, Masood Tariq

Procedia Computer Science Vol 277, pp. 2709-2722 (2026)

https://doi.org/10.1016/j.procs.2026.02.308

Prototype distance ratio sampling for generalised few shot object detection

Lekkas Alessandro, Roper Marc, Abel Andrew

Pattern Recognition Letters Vol 204, pp. 1-7 (2026)

https://doi.org/10.1016/j.patrec.2026.03.014

Affective state recognition in online learning : A deep learning approach with data augmentation

Devasya Ashwitha, Abel Andrew, Wang Yuchen, Jia Laibing

2025 20th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) 20th International Workshop on Semantic and Social Media Adaptation & Personalization, pp. 108-113 (2025)

https://doi.org/10.1109/SMAP66932.2025.00027

Classroom engagement analysis and feedback using MER

Devasya Ashwitha, Abel Andrew, Wang Yuchen, Jia Laibing

BERA Annual Conference 2025 (2025)

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Professional Activities

BERA Annual Conference 2025

Speaker

9/2025

MND Scotland (External organisation)

Member

2/6/2025

Remember the Humans

Speaker

8/4/2025

MND Scotland (External organisation)

Member

5/2/2025

Multimodal Communication: Machine Learning for Speech and Lipreading

Invited speaker

29/11/2024

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Projects

AI for Reading Improvement: Measuring Learning Outcomes with Spark Education AI

Zhao, Yingying (Principal Investigator) Abel, Andrew (Co-investigator)

06-Jan-2026 - 22-Jan-2026

Developing teaching professionals’ knowledge and skills in AI technologies for inclusive and equitable education

Wang, Yuchen (Principal Investigator) Abel, Andrew (Co-investigator) Jia, Laibing (Co-investigator) Ul Ain, Noor (Researcher) Mevawalla, Zinnia (Co-investigator) Catlin, Jane (Co-investigator) Devasya, Ashwitha (Researcher) Tripathy, Aditi (Researcher) Nikou, Stavros (Co-investigator) Roxburgh, David (Co-investigator) Robinson, Deborah (Co-investigator)

This project is to co-design a professional learning programme on AI and inclusive education with teachers and student teachers, funded by EPSRC (£9,961).

01-Jan-2025 - 31-Jan-2026

AI-Based Translation of Dog Behaviour, Emotion, and Intention

Abel, Andrew (Principal Investigator) Zhao, Yingying (Co-investigator)

A feasibility study into the use of AI to analyse dog behaviour. Funded by Innovation Voucher.

20-Jan-2025 - 19-Jan-2025

Human-centred AI Technologies for Inclusion in Education and Society

Abel, Andrew (Principal Investigator) Wang, Yuchen (Principal Investigator) Jia, Laibing (Principal Investigator)

Strathclyde Centre for Doctoral Training 2023 (approx. £260,000)

01-Jan-2023 - 30-Jan-2027

Towards visually-driven speech enhancement for cognitively-inspired multi-modal hearing-aid devices (AV-COGHEAR)

Abel, Andrew (Research Co-investigator)

This ambitious project aimed to develop a new generation of hearing aid technology that extracts speech from noise by using a camera to see what the talker is saying. The wearer of the device will be able to focus their hearing on a target talker and the device will filter out competing sound. This ability, which is beyond that of current technology, has the potential to improve the quality of life of the millions suffering from hearing loss (over 10m in the UK alone). Our approach was consistent with normal hearing. Listeners naturally combine information from both their ears and eyes: we use our eyes to help us hear. When listening to speech, eyes follow the movements of the face and mouth and a sophisticated, multi-stage process uses this information to separate speech from the noise and fill in any gaps. Our proposed approach was much the same. We exploit visual information from a camera, and novel algorithms for intelligently combining audio and visual information, in order to improve speech quality and intelligibility in real-world noisy environments.

01-Jan-2016 - 31-Jan-2019

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