{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,14]],"date-time":"2025-12-14T16:14:02Z","timestamp":1765728842385,"version":"3.40.5"},"reference-count":20,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T00:00:00Z","timestamp":1642982400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Communication University of Zhejiang"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2022,1,24]]},"abstract":"<jats:p>With the continuous development of social economy, film and television animation, as the spiritual needs of ordinary people, is more and more popular. Especially for the development of emerging technologies, the corresponding voice can be used to change AI expression. But at the same time, how to ensure the synchronization of language sound and facial expression is one of the difficulties in animation transformation. Relying on the compromised node detection of wireless sensor networks, this paper combs the synchronous traffic flow between the speech signals and facial expressions, finds the pattern distribution of facial motion based on unsupervised classification, realizes training and learning through neural networks, and realizes one-to-one mapping to facial expressions by using the rhyme distribution of speech features. It avoids the defect of robustness of speech recognition, improves the learning ability of speech recognition, and realizes the driving analysis of facial expression film and television animation. The simulation results show that the compromised node detection in wireless sensor networks is effective and can support the analysis and research of speech-driven facial expression film and television animation.<\/jats:p>","DOI":"10.1155\/2022\/8563818","type":"journal-article","created":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T03:05:07Z","timestamp":1643079907000},"page":"1-8","source":"Crossref","is-referenced-by-count":2,"title":["Research on Voice-Driven Facial Expression Film and Television Animation Based on Compromised Node Detection in Wireless Sensor Networks"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1519-1079","authenticated-orcid":true,"given":"Shi-Jiang","family":"Wen","sequence":"first","affiliation":[{"name":"Department of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea"},{"name":"Department of Xinjiang Art and Sports, Ningbo Childhood Education College, Ningbo 315016, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1951-6651","authenticated-orcid":true,"given":"Hao","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea"},{"name":"School of Animation and Digital Arts, Communication University of Zhejiang, Hangzhou 310018, China"}]},{"given":"Jong-Hoon","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1186\/s40886-016-0014-9"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2016.03.001"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0193(200002)9:2<93::AID-HBM4>3.0.CO;2-Z"},{"issue":"6","key":"4","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1016\/S1053-8119(01)91801-4","article-title":"Time courses of left and right amygdalar responses to fearful facial expressions","volume":"13","author":"M. 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