IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Opportunistic Detection Methods for Emotion-Aware Smartphone Applications

Opportunistic Detection Methods for Emotion-Aware Smartphone Applications
View Sample PDF
Author(s): Igor Bisio (University of Genoa, Italy), Alessandro Delfino (University of Genoa, Italy), Fabio Lavagetto (University of Genoa, Italy) and Mario Marchese (University of Genoa, Italy)
Copyright: 2014
Pages: 33
Source title: Creating Personal, Social, and Urban Awareness through Pervasive Computing
Source Author(s)/Editor(s): Bin Guo (Northwestern Polytechnical University, China), Daniele Riboni (University of Milano, Italy) and Peizhao Hu (NICTA, Australia)
DOI: 10.4018/978-1-4666-4695-7.ch003

Purchase

View Opportunistic Detection Methods for Emotion-Aware Smartphone Applications on the publisher's website for pricing and purchasing information.

Abstract

Human-machine interaction is performed by devices such as the keyboard, the touch-screen, or speech-to-text applications. For example, a speech-to-text application is software that allows the device to translate the spoken words into text. These tools translate explicit messages but ignore implicit messages, such as the emotional status of the speaker, filtering out a portion of information available in the interaction process. This chapter focuses on emotion detection. An emotion-aware device can also interact more personally with its owner and react appropriately according to the user’s mood, making the user-machine interaction less stressful. The chapter gives the guidelines for building emotion-aware smartphone applications in an opportunistic way (i.e., without the user’s collaboration). In general, smartphone applications might be employed in different contexts; therefore, the to-be-detected emotions might be different.

Related Content

Bin Guo, Yunji Liang, Zhu Wang, Zhiwen Yu, Daqing Zhang, Xingshe Zhou. © 2014. 20 pages.
Yunji Liang, Xingshe Zhou, Bin Guo, Zhiwen Yu. © 2014. 31 pages.
Igor Bisio, Alessandro Delfino, Fabio Lavagetto, Mario Marchese. © 2014. 33 pages.
Kobkaew Opasjumruskit, Jesús Expósito, Birgitta König-Ries, Andreas Nauerz, Martin Welsch. © 2014. 22 pages.
Viktoriya Degeler, Alexander Lazovik. © 2014. 23 pages.
Vlasios Kasapakis, Damianos Gavalas. © 2014. 26 pages.
Zhu Wang, Xingshe Zhou, Daqing Zhang, Bin Guo, Zhiwen Yu. © 2014. 18 pages.
Body Bottom