Full metadata record
DC FieldValueLanguage
dc.contributor.authorHuang, Xun-Yien_US
dc.contributor.authorCherng, Fu-Yinen_US
dc.contributor.authorKing, Jung-Taien_US
dc.contributor.authorLin, Wen-Chiehen_US
dc.date.accessioned2020-10-05T02:01:30Z-
dc.date.available2020-10-05T02:01:30Z-
dc.date.issued2019-01-01en_US
dc.identifier.isbn978-1-4503-6825-4en_US
dc.identifier.urihttp://dx.doi.org/10.1145/3338286.3340139en_US
dc.identifier.urihttp://hdl.handle.net/11536/155285-
dc.description.abstractAuditory saliency is an important mechanism that helps humans extract relevant information from environments. Audio notifications of mobile devices with high saliency can increase users' receptivity, yet overly high saliency could cause annoyance. Accurately measuring auditory saliency of a notification is critical for evaluating its usability. Previous studies adopted behavioral methods. However, their results may not accurately reflect auditory saliency as humans' perception of auditory saliency often involves complicated cognitive processes. Thus, we propose an electroencephalography (EEG)-based approach that can complement behavioral studies to provide a more nuanced analysis of auditory saliency. We evaluated our method by conducting an EEG experiment that measured the mismatch negativity and P3a of the sounds in realistic scenarios. We also conducted a behavioral experiment to link the EEG-based method with the behavioral method. The results suggested that EEG can provide detailed information about how human perceive auditory saliency and complement the behavioral measures.en_US
dc.language.isoen_USen_US
dc.subjectAuditory Saliencyen_US
dc.subjectNotificationen_US
dc.subjectBrain-computer Interfaceen_US
dc.titleEEG-based Measures of Auditory Saliency in a Complex Contexten_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1145/3338286.3340139en_US
dc.identifier.journalPROCEEDINGS OF THE 21ST INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION WITH MOBILE DEVICES AND SERVICES (MOBILEHCI'19)en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.department腦科學研究中心zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentBrain Research Centeren_US
dc.identifier.wosnumberWOS:000556723600028en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper