مؤتمر
Exploring automatic covid-19 diagnosis via voice and symptoms from crowdsourced data
| العنوان: | Exploring automatic covid-19 diagnosis via voice and symptoms from crowdsourced data |
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| المؤلفون: | Han, J, Brown, C, Chauhan, J, Grammenos, A, Hasthanasombat, A, Spathis, D, Xia, T, Cicuta, P, Mascolo, C |
| بيانات النشر: | IEEE //dx.doi.org/10.1109/icassp39728.2021.9414576 ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| سنة النشر: | 2021 |
| المجموعة: | Apollo - University of Cambridge Repository |
| مصطلحات موضوعية: | COVID-19, Crowdsourced data, Speech analysis, Symptoms analysis |
| الوصف: | The development of fast and accurate screening tools, which could facilitate testing and prevent more costly clinical tests, is key to the current pandemic of COVID-19. In this context, some initial work shows promise in detecting diagnostic signals of COVID-19 from audio sounds. In this paper, we propose a voice-based framework to automatically detect individuals who have tested positive for COVID-19. We evaluate the performance of the proposed framework on a subset of data crowdsourced from our app, containing 828 samples from 343 participants. By combining voice signals and reported symptoms, an AUC of 0.79 has been attained, with a sensitivity of 0.68 and a specificity of 0.82. We hope that this study opens the door to rapid, low-cost, and convenient pre-screening tools to automatically detect the disease. ; ERC Project 833296 (EAR) |
| نوع الوثيقة: | conference object |
| وصف الملف: | application/pdf |
| اللغة: | English |
| العلاقة: | https://www.repository.cam.ac.uk/handle/1810/317768Test |
| DOI: | 10.17863/CAM.64882 |
| الإتاحة: | https://doi.org/10.17863/CAM.64882Test https://www.repository.cam.ac.uk/handle/1810/317768Test |
| حقوق: | All rights reserved |
| رقم الانضمام: | edsbas.26409151 |
| قاعدة البيانات: | BASE |
| DOI: | 10.17863/CAM.64882 |
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