Dr Ning Ma

About

Ning is a Lecturer in Medical Computing at the School of Computer Science, University of Sheffield, and also an Academic Directorate of Medical Imaging and Medical Physics at the Sheffield Teaching Hospitals NHS Foundation Trust. Before that he was a Research Fellow in Computer Science working on health-related research projects. His first degree was in Computer Science from South China University of Technology and he has a PhD in hearing inspired automatic speech processing from the University of Sheffield.Ning’s research interests lie in speech and hearing technologies, machine learning and healthcare. In particular, his research interests focus on development of AI systems that can interpret sounds and low-cost sensor data and extract useful information for screening health issues, such

Selected publications

• Romero HE, Ma N, Brown G & Hill EA (2022) Acoustic screening for obstructive sleep apnea in home environments based on deep neural networks. IEEE Journal of Biomedical and Health Informatics, 26(7), 2941-2950. View this article in WRRO
• Ma N, May T & Brown GJ (2017) Exploiting Deep Neural Networks and Head Movements for Robust Binaural Localisation of Multiple Sources in Reverberant Environments. IEEE Transactions on Audio, Speech, and Language Processing, 25(12), 2444-2453. View this article in WRRO
• Ma N, Morris S & Kitterick PT (2016) Benefits to Speech Perception in Noise From the Binaural Integration of Electric and Acoustic Signals in Simulated Unilateral Deafness. Ear and Hearing, 37(3), 248-259. View this article in WRRO
• Romero HE, Ma N, Brown GJ & Johnson S (2023) Obstructive sleep apnea screening with breathing sounds and respiratory effort: a multimodal deep learning approach. Interspeech 2023 Proceedings (pp 5451-5455). Dublin, Ireland, 20 August 2023 - 20 August 2023. View this article in WRRO
• Hu Q, Ma N & Brown GJ (2023) Robust binaural sound localisation with temporal attention. ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Proceedings. Rhodes Island, Greece, 4 June 2023 - 4 June 2023. View this article in WRRO
• Tu Z, Deadman J, Ma N & Barker J (2022) Auditory-Based Data Augmentation for end-to-end Automatic Speech Recognition. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp 7447-7451), 23 May 2022 - 27 May 2022.
• Tu Z, Ma N & Barker J (2021) Optimising hearing aid fittings for speech in noise with a differentiable hearing loss model. Interspeech 2021 (pp 691-695). Brno, Czechia, 30 August 2021 - 30 August 2021. View this article in WRRO
• Ornolfsson I, Dau T, Ma N & May T (2021) Exploiting Non-Negative Matrix Factorization for Binaural Sound Localization in the Presence of Directional Interference. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp 221-225), 6 June 2021 - 11 June 2021.
• Romero HE, Ma N, Hill EA & Brown GJ (2020) 0573 Screening for obstructive sleep apnea at home based on deep learning features derived from respiration sounds. Sleep, Vol. 43(Supplement_1) (pp a219-a220). Philadelphia, PA, USA (online conference), 27 August 2020 - 27 August 2020. View this article in WRRO
• Romero HE, Ma N & Brown GJ (2020) Snorer diarisation based on deep neural network embeddings. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Barcelona, Spain (virtual conference), 4 May 2020 - 4 May 2020. View this article in WRRO