| End-2-end covid-19 detection from breath & cough audio H Coppock, A Gaskell, P Tzirakis, A Baird, L Jones, BW Schuller arXiv preprint arXiv:2102.08359, 2021 | 114 | 2021 |
| Detecting COVID-19 from breathing and coughing sounds using deep neural networks MA Nessiem, MM Mohamed, H Coppock, A Gaskell, BW Schuller 2021 IEEE 34th International Symposium on Computer-Based Medical Systems …, 2021 | 75* | 2021 |
| COVID-19 detection from audio: seven grains of salt H Coppock, L Jones, I Kiskin, B Schuller The Lancet Digital Health 3 (9), e537-e538, 2021 | 52 | 2021 |
| The ACM multimedia 2022 computational paralinguistics challenge: Vocalisations, stuttering, activity, & mosquitoes B Schuller, A Batliner, S Amiriparian, C Bergler, M Gerczuk, N Holz, ... Proceedings of the 30th ACM International Conference on Multimedia, 7120-7124, 2022 | 33 | 2022 |
| Evaluating the covid-19 identification resnet (cider) on the interspeech covid-19 from audio challenges A Akman, H Coppock, A Gaskell, P Tzirakis, L Jones, BW Schuller Frontiers in digital health 4, 789980, 2022 | 19 | 2022 |
| Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers H Coppock, G Nicholson, I Kiskin, V Koutra, K Baker, J Budd, R Payne, ... Nature Machine Intelligence, 1-14, 2024 | 9 | 2024 |
| A summary of the ComParE COVID-19 challenges H Coppock, A Akman, C Bergler, M Gerczuk, C Brown, J Chauhan, ... Frontiers in Digital Health 5, 1058163, 2023 | 7 | 2023 |
| Audio barlow twins: Self-supervised audio representation learning J Anton, H Coppock, P Shukla, BW Schuller ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 5 | 2023 |
| A large-scale and PCR-referenced vocal audio dataset for COVID-19 J Budd, K Baker, E Karoune, H Coppock, S Patel, AT Cañadas, A Titcomb, ... arXiv preprint arXiv:2212.07738, 2022 | 3 | 2022 |
| Climate change & computer audition: A call to action and overview on audio intelligence to help save the planet BW Schuller, A Akman, Y Chang, H Coppock, A Gebhard, A Kathan, ... arXiv preprint arXiv:2203.06064, 2022 | 3 | 2022 |
| Statistical design and analysis for robust machine learning: a case study from COVID-19 D Pigoli, K Baker, J Budd, L Butler, H Coppock, S Egglestone, SG Gilmour, ... arXiv preprint arXiv:2212.08571, 2022 | 2 | 2022 |
| Ecology & computer audition: Applications of audio technology to monitor organisms and environment BW Schuller, A Akman, Y Chang, H Coppock, A Gebhard, A Kathan, ... Heliyon, 2023 | 1 | 2023 |
| Artificial intelligence in COVID-19 MA Nessiem, H Coppock, MM Mohamed, BW Schuller Omics approaches and technologies in COVID-19, 255-273, 2023 | 1 | 2023 |
| Bias and privacy in AI's cough-based COVID-19 recognition–Authors' reply H Coppock, L Jones, I Kiskin, B Schuller The Lancet Digital Health 3 (12), e761, 2021 | 1 | 2021 |
| Synthia’s Melody: A Benchmark Framework for Unsupervised Domain Adaptation in Audio CH Lin, C Jones, BW Schuller, H Coppock, A Akman ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| Audio-based AI classifiers show no evidence of improved COVID-19 diagnosis over simple symptom checkers H Coppock, G Nicholson, I Kiskin, V Koutra, K Baker, J Budd, R Payne, ... Nature Machine Intelligence, 0 | | |
Björn SchullerProfessor, Technische Universität München (TUM) / Imperial College London & CSO, audEERINGVerified email at tum.de
