Opportunistic Detection Methods for Emotion-Aware Smartphone Applications

Author:

Bisio Igor1,Delfino Alessandro1,Lavagetto Fabio1,Marchese Mario1

Affiliation:

1. University of Genoa, Italy

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.

Publisher

IGI Global

Reference101 articles.

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2. Agneessens, A., Bisio, I., Lavagetto, F., Marchese, M., & Sciarrone, A. (2010). Speaker Count application for smartphone platforms. Wireless Pervasive Computing (ISWPC), 2010 5th IEEE International Symposium on, (pp. 361-366). Modena.

3. Ang, J. R. D. (2002). Prosody-based automatic detection of annoyance and frustration in human computer dialog. Proc. Int. Conf. Spoken Language Processing (ICSLP ’02), (pp. 2037-2040).

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