Acta Marisiensis.
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Year 2024
Volume 21 (XXXVIII), no 1 Year 2023 Volume 20 (XXXVII), no 1 Volume 20 (XXXVII), no 2 Year 2022 Volume 19 (XXXVI), no 1 Volume 19 (XXXVI), no 2 Year 2021 Volume 18 (XXXV), no 1 Volume 18 (XXXV), no 2 Year 2020 Volume 17 (XXXIV), no 1 Volume 17 (XXXIV), no 2 Year 2019 Volume 16 (XXXIII), no 1 Volume 16 (XXXIII), no 2 Year 2018 Volume 15 (XXXII), no 1 Volume 15 (XXXII), no 2 Year 2017 Volume 14 (XXXI), no 1 Volume 14 (XXXI), no 2 Year 2016 Volume 13 (XXX), no 1 Volume 13 (XXX), no 2 Year 2015 Volume 12 (XXIX), no 1 Volume 12 (XXIX), no 2 Year 2014 Volume 11 (XXVIII), no 1 Volume 11 (XXVIII), no 2 Year 2013 Volume 10 (XXVII), no 1 Volume 10 (XXVII), no 2 Year 2012 Volume 9 (XXVI), no 1 Volume 9 (XXVI), no 2 Year 2011 Volume 8 (XXV), no 1 Volume 8 (XXV), no 2 Year 2010 Volume 7 (XXIV), no 1 Volume 7 (XXIV), no 2 Year 2009 Volume 6 (XXIII) |
2023, Volume 20 (XXXVII), no 1
Roland KILIK, University of Miskolc, Hungary Abstract: Human-like agents are becoming more and more common. However, the usefulness of these agents depends to a large extent on the naturalness of their movements. The classification procedure presented in this article aims to increase the naturalness of the head movements of human-like agents. The method is capable of estimating the vertical range of head movement from the speech sound alone, and thus allows a final phase amplitude correction of the generated head movements of virtual talking heads in order to increase naturalness. The advantage of the method, is that it does not require visual information, works for general subjects, its precision and effectiveness can be improved by defining further classes, and it can improve the naturalness of any head movement generation method’s output by a posterior amplitude scaling. DOI: https://doi.org/10.2478/amset-2023-0001 Pages: 1-9 View full article |
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Update: 19-Jun-2024 | © Published by University Press |