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Talking Avatar: An Intelligent Mobile Application Based on Third-Party Cloud Services

Talking Avatar: An Intelligent Mobile Application Based on Third-Party Cloud Services

Feng Ye, Qian Huang, Shengyan Wu, Yong Chen
Copyright: © 2019 |Volume: 15 |Issue: 3 |Pages: 13
ISSN: 1548-3908|EISSN: 1548-3916|EISBN13: 9781522564164|DOI: 10.4018/IJTHI.2019070101
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MLA

Ye, Feng, et al. "Talking Avatar: An Intelligent Mobile Application Based on Third-Party Cloud Services." IJTHI vol.15, no.3 2019: pp.1-13. http://doi.org/10.4018/IJTHI.2019070101

APA

Ye, F., Huang, Q., Wu, S., & Chen, Y. (2019). Talking Avatar: An Intelligent Mobile Application Based on Third-Party Cloud Services. International Journal of Technology and Human Interaction (IJTHI), 15(3), 1-13. http://doi.org/10.4018/IJTHI.2019070101

Chicago

Ye, Feng, et al. "Talking Avatar: An Intelligent Mobile Application Based on Third-Party Cloud Services," International Journal of Technology and Human Interaction (IJTHI) 15, no.3: 1-13. http://doi.org/10.4018/IJTHI.2019070101

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Abstract

With the booming of the mobile computing and web technology, virtual and intelligent mobile applications become increasingly popular, e.g. web computing and web-based information retrieval. However, under contemporary network conditions and web application environment, it remains a challenging problem to achieve a trade-off between algorithm complexity and hardware performance. In this article, a Talking Avatar architecture is presented based on third-party cloud services. First, the authors propose a cloud service based multi-level layered software framework, which consists of user interface layer, business logic layer and data layer. Second, human face synthesis, speech conversion and social sharing schemes are introduced to integrate third-party cloud services. Third, experimental results on Android platforms indicate that the proposed Talking Avatar can be served efficiently in terms of memory consumption as well as average response time. In addition, stronger functions are provided compared with existing methods.

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