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http://bura.brunel.ac.uk/handle/2438/29288
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DC Field | Value | Language |
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dc.contributor.author | Datta, S | - |
dc.contributor.author | Aondoakaa, A | - |
dc.contributor.author | Holmberg, JJ | - |
dc.contributor.author | Antonova, E | - |
dc.coverage.spatial | Singapore | - |
dc.date.accessioned | 2024-07-03T08:10:04Z | - |
dc.date.available | 2024-07-03T08:10:04Z | - |
dc.date.issued | 2022-04-27 | - |
dc.identifier | ORCiD: Elena Antonova https://orcid.org/0000-0003-1624-3202 | - |
dc.identifier.citation | Datta, S. et al. (2022) 'Recognition Of Silently Spoken Word From Eeg Signals Using Dense Attention Network (DAN)', ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, 23-27 May, pp. 4558 - 4562. doi: 10.1109/icassp43922.2022.9746241. | en_US |
dc.identifier.isbn | 978-1-6654-0540-9 (ebk) | - |
dc.identifier.isbn | 978-1-6654-0541-6 (PoD) | - |
dc.identifier.issn | 1520-6149 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29288 | - |
dc.description.abstract | In this paper, we propose a method for recognizing silently spoken words from electroencephalogram (EEG) signals using a Dense Attention Network (DAN). The proposed network learns features from the EEG data by applying the self-attention mechanism on temporal, spectral, and spatial (electrodes) dimensions. We examined the effectiveness of the proposed network in extracting spatio-spectro-temporal in-formation from EEG signals and provide a network for recognition of silently spoken words. The DAN achieved a recognition rate of 80.7% in leave-trials-out (LTO) and 75.1% in leave-subject-out (LSO) cross validation methods. In a direct comparison with other methods, the DAN outperformed other existing techniques in recognition of silently spoken words. | en_US |
dc.format.extent | 4558 - 4562 | - |
dc.format.medium | Print-Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.rights | Copyright © 2022 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works (see: https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/). | - |
dc.rights.uri | https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/ | - |
dc.source | ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | - |
dc.source | ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | - |
dc.source | ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | - |
dc.source | ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | - |
dc.subject | brain computer interface (BCI) | en_US |
dc.subject | silently spoken speech | en_US |
dc.subject | attention mechanism | en_US |
dc.subject | electroencephalogram (EEG) | en_US |
dc.title | Recognition Of Silently Spoken Word From Eeg Signals Using Dense Attention Network (DAN) | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | https://doi.org/10.1109/icassp43922.2022.9746241 | - |
dc.relation.isPartOf | ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | - |
pubs.finish-date | 2022-05-27 | - |
pubs.finish-date | 2022-05-27 | - |
pubs.finish-date | 2022-05-27 | - |
pubs.finish-date | 2022-05-27 | - |
pubs.publication-status | Published | - |
pubs.start-date | 2022-05-23 | - |
pubs.start-date | 2022-05-23 | - |
pubs.start-date | 2022-05-23 | - |
pubs.start-date | 2022-05-23 | - |
dc.identifier.eissn | 2379-190X | - |
dc.rights.holder | Institute of Electrical and Electronics Engineers (IEEE) | - |
Appears in Collections: | Dept of Life Sciences Research Papers |
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