{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T10:39:26Z","timestamp":1784543966289,"version":"3.55.0"},"reference-count":37,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T00:00:00Z","timestamp":1633910400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this work, we focus on silent speech recognition in electroencephalography (EEG) data of healthy individuals to advance brain\u2013computer interface (BCI) development to include people with neurodegeneration and movement and communication difficulties in society. Our dataset was recorded from 270 healthy subjects during silent speech of eight different Russia words (commands): \u2018forward\u2019, \u2018backward\u2019, \u2018up\u2019, \u2018down\u2019, \u2018help\u2019, \u2018take\u2019, \u2018stop\u2019, and \u2018release\u2019, and one pseudoword. We began by demonstrating that silent word distributions can be very close statistically and that there are words describing directed movements that share similar patterns of brain activity. However, after training one individual, we achieved 85% accuracy performing 9 words (including pseudoword) classification and 88% accuracy on binary classification on average. We show that a smaller dataset collected on one participant allows for building a more accurate classifier for a given subject than a larger dataset collected on a group of people. At the same time, we show that the learning outcomes on a limited sample of EEG-data are transferable to the general population. Thus, we demonstrate the possibility of using selected command-words to create an EEG-based input device for people on whom the neural network classifier has not been trained, which is particularly important for people with disabilities.<\/jats:p>","DOI":"10.3390\/s21206744","type":"journal-article","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T21:45:32Z","timestamp":1633988732000},"page":"6744","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["Silent EEG-Speech Recognition Using Convolutional and Recurrent Neural Network with 85% Accuracy of 9 Words Classification"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5640-925X","authenticated-orcid":false,"given":"Darya","family":"Vorontsova","sequence":"first","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"},{"name":"Software Engineering Department, National Research University of Electronic Technology (MIET), 124498 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9987-4060","authenticated-orcid":false,"given":"Ivan","family":"Menshikov","sequence":"additional","affiliation":[{"name":"Faculty of Mechanics and Mathematics, Moscow State University, GSP-1, 1 Leninskiye Gory, Main Building, 119991 Moscow, Russia"},{"name":"Department of Control and Applied Mathematics, Moscow Institute of Physics and Technology (MIPT), 141700 Dolgoprudny, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1060-9253","authenticated-orcid":false,"given":"Aleksandr","family":"Zubov","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"},{"name":"Department of Information Technologies and Computer Sciences, National University of Science and Technology MISIS (NUST MISIS), 119049 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4832-6689","authenticated-orcid":false,"given":"Kirill","family":"Orlov","sequence":"additional","affiliation":[{"name":"Research Center of Endovascular Neurosurgery, Federal State Budgetary Institution \u201cFederal Center of Brain Research and Neurotechnologies\u201d of the Federal Medical Biological Agency, Ostrovityanova Street, 1, p. 10, 117997 Moscow, Russia"},{"name":"Russia Endovascular Neuro Society (RENS), 107078 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Rikunov","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8800-1344","authenticated-orcid":false,"given":"Ekaterina","family":"Zvereva","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lev","family":"Flitman","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anton","family":"Lanikin","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Sokolova","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0036-8214","authenticated-orcid":false,"given":"Sergey","family":"Markov","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8835-6583","authenticated-orcid":false,"given":"Alexandra","family":"Bernadotte","sequence":"additional","affiliation":[{"name":"Experimental ML Systems Subdivision, SberDevices Department, PJSC Sberbank, 121165 Moscow, Russia"},{"name":"Faculty of Mechanics and Mathematics, Moscow State University, GSP-1, 1 Leninskiye Gory, Main Building, 119991 Moscow, Russia"},{"name":"Department of Information Technologies and Computer Sciences, National University of Science and Technology MISIS (NUST MISIS), 119049 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Graimann, B., Pfurtscheller, G., and Allison, B. 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