ID | 118255 |
Author |
Liu, Zheng
Tokushima University
Ren, Fuji
Tokushima University
Tokushima University Educator and Researcher Directory
KAKEN Search Researchers
|
Keywords | Lip matching
Vowel priority
Similarity evaluation
Humanoid robot
Manhattan distance
|
Content Type |
Journal Article
|
Description | At present, the significance of humanoid robots dramatically increased while this kind of robots rarely enters human life because of its immature development. The lip shape of humanoid robots is crucial in the speech process since it makes humanoid robots look like real humans. Many studies show that vowels are the essential elements of pronunciation in all languages in the world. Based on the traditional research of viseme, we increased the priority of the smooth transition of lip between vowels and propose a lip matching scheme based on vowel priority. Additionally, we also designed a similarity evaluation model based on the Manhattan distance by using computer vision lip features, which quantifies the lip shape similarity between 0-1 provides an effective recommendation of evaluation standard. Surprisingly, this model successfully compensates the disadvantages of lip shape similarity evaluation criteria in this field. We applied this lip-matching scheme to Ren-Xin humanoid robot and performed robot teaching experiments as well as a similarity comparison experiment of 20 sentences with two males and two females and the robot. Notably, all the experiments have achieved excellent results.
|
Journal Title |
Journal of Ambient Intelligence and Humanized Computing
|
ISSN | 18685145
18685137
|
Publisher | Springer Nature
|
Volume | 13
|
Issue | 11
|
Start Page | 5055
|
End Page | 5066
|
Published Date | 2020-06-11
|
Remark | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s12652-020-02175-9
|
EDB ID | |
DOI (Published Version) | |
URL ( Publisher's Version ) | |
FullText File | |
language |
eng
|
TextVersion |
Author
|
departments |
Science and Technology
|