Modeling Reader's Emotional State Response on Document's Typographic Elements

Dimitrios Tsonos,Georgios Kouroupetroglou

doi:10.1155/2011/206983

Dimitrios Tsonos, Georgios Kouroupetroglou

Open Access

https://doi.org/10.1155/2011/206983

Copy DOI

Abstract

We present the results of an experimental study towards modeling the reader's emotional state variations induced by the typographic elements in electronic documents. Based on the dimensional theory of emotions we investigate how typographic elements, like font style (bold, italics, bold-italics) and font (type, size, color and background color), affect the reader's emotional states, namely, Pleasure, Arousal, and Dominance (PAD). An experimental procedure was implemented conforming to International Affective Picture System guidelines and incorporating the Self-Assessment Manikin test. Thirty students participated in the experiment. The stimulus was a short paragraph of text for which any content, emotion, and/or domain dependent information was excluded. The Analysis of Variance revealed the dependency of (a) all the three emotional dimensions on font size and font/background color combinations and (b) the Pleasure dimension on font type and font style. We introduce a set of mapping rules showing how PAD vary on the discrete values of font style and font type elements. Moreover, we introduce a set of equations describing the PAD dimensions' dependency on font size. This novel model can contribute to the automated reader's emotional state extraction in order, for example, to enhance the acoustic rendition of the documents, utilizing text-to-speech synthesis.

Highlights

Most of the current Text-to-Speech systems do not take into account the semantics and the cognitive aspects of the visual and nonvisual document elements
There is an effort towards Documentto-Audio (DtA) synthesis, which essentially constitutes the generation of the Text-to-Speech systems, supporting the extraction of the semantics of document metadata [1] and the efficient acoustic representation of both text formatting [2,3,4,5] and data tables [6,7,8] through the modeling of the parameters of the synthesized speech signal by: (a) combining alternative text insertion in the document text stream, (b) altering the prosody, (c) switching between voices, and/or (d) inserting nonspeech audio in the waveform stream, according to the class of metadata provided in the document
In order to study how the font/background color combinations affect the emotional states using various font types and font style elements, we investigate the following combinations using 16 px (5.28 mm) font size text: plain, bold and bold-italics for the case of Times New Roman and bold, bold-italics for Arial

Summary

Introduction

Most of the current Text-to-Speech systems do not take into account the semantics and the cognitive aspects of the visual (such as font and font style) and nonvisual document elements. Most of the studies (presented ) focus on the qualitative description of the way typographic elements affect the reader’s emotional state and propose or suggest how the typographic elements should be used while creating a document (e.g., web pages, leaflets, and scientific documents). They do not fulfill the requirements for a more formal description using mathematical modeling in order to be used in DtA synthesis and in other systems, such as those presented in [10, 11]. They concluded that 14 pt font size (compared to 12 pt) was more preferable and the Simplified Arabic font type (easy and fast to read) and Arial (attractive) were preferred among five font types

Methods

Results

Discussion

Conclusion