Construction of UEQ+ scales for voice quality: measuring user experience quality of voice interaction

The UEQ+ is a modular framework for the construction of UX questionnaires. The researcher can pick those scales that fit his or her research question from a list of 16 available UX scales. Currently, no UEQ+ scales are available to allow measuring the quality of voice interactions. Given that this type of interaction is increasingly essential for the usage of digital products, this is a severe limitation of the possible products and usage scenarios that can be evaluated using the UEQ+. We describe in this paper the construction of three specific scales to measure the UX of voice interactions. Besides, we discuss how these new scales can be combined with existing UEQ+ scales in evaluation projects.

[1]  Alexandre N. Tuch,et al.  Is beautiful really usable? Toward understanding the relation between usability, aesthetics, and affect in HCI , 2012, Comput. Hum. Behav..

[2]  C M Pollock,et al.  The influence of sustained attention on railway accidents. , 1997, Accident; analysis and prevention.

[3]  Tetsuo Kida,et al.  Changes in arousal level by differential exercise intensity , 2004, Clinical Neurophysiology.

[4]  Yang Wang,et al.  Using galvanic skin response for cognitive load measurement in arithmetic and reading tasks , 2012, OZCHI.

[5]  Heather E. K. Rodd.  Roadside Advertisements: Effects of Valence and Arousal on Driver Performance , 2017 .

[6]  P. Salovey,et al.  The wisdom in feeling: psychological processes in emotional intelligence , 2002 .

[7]  S. Watanuki,et al.  Effects of reduction in arousal level caused by long-lasting task on CNV. , 1997, Applied human science : journal of physiological anthropology.

[8]  Marshall Scott Poole,et al.  Aesthetic design of e-commerce web pages - Webpage Complexity, Order and preference , 2012, Electron. Commer. Res. Appl..

[9]  Stojan Trajanovski,et al.  Deep Physiological Arousal Detection in a Driving Simulator Using Wearable Sensors , 2017, 2017 IEEE International Conference on Data Mining Workshops (ICDMW).

[10]  Jonathon Love,et al.  JASP: Graphical Statistical Software for Common Statistical Designs , 2019, Journal of Statistical Software.

[11]  Bryan Reimer,et al.  Driver wellness, safety and the development of an AwareCar , 2009 .

[12]  B. Tversky,et al.  Effects of visual and verbal presentation on cognitive load in vigilance, memory, and arithmetic tasks. , 2011, Psychophysiology.

[13]  M. Bradley,et al.  The pupil as a measure of emotional arousal and autonomic activation. , 2008, Psychophysiology.

[14]  C. Stepp,et al.  Acoustic Measures of Voice and Physiologic Measures of Autonomic Arousal during Speech as a Function of Cognitive Load. , 2017, Journal of voice : official journal of the Voice Foundation.

[15]  Gabriel J. Biehal,et al.  Memory-Based Inferences during Consumer Choice , 1990 .

[16]  Hartmut Wandke,et al.  Was verursacht den Zusammenhang zwischen Ästhetik und Usability , 2009 .

[17]  R. Yerkes,et al.  The relation of strength of stimulus to rapidity of habit‐formation , 1908 .

[18]  Noam Tractinsky,et al.  Aesthetics and apparent usability: empirically assessing cultural and methodological issues , 1997, CHI.

[19]  G E Raney,et al.  Monitoring changes in cognitive load during reading: an event-related brain potential and reaction time analysis. , 1993, Journal of experimental psychology. Learning, memory, and cognition.

[20]  Martin Schrepp,et al.  Übersichtlichkeit als Mediator zwischen Ästhetik und Usability? , 2015, MuC.

[21]  Melanie D. Polkosky.  Machines as mediators: The challenge of technology for interpersonal communication theory and research , 2008 .

[22]  Steven Shorrock,et al.  Errors of perception in air traffic control , 2007 .

[23]  Meinald T. Thielsch,et al.  Visual Aesthetics and Performance: A First Meta-Analysis , 2019, MuC.

[24]  James R. Lewis,et al.  Expanding the MOS: Development and Psychometric Evaluation of the MOS-R and MOS-X , 2003, Int. J. Speech Technol..

[25]  R. Haines,et al.  Experimental investigation on the effects of website aesthetics on user performance in different virtual tasks , 2019, PeerJ.

[26]  Jörg Thomaschewski,et al.  Design and Validation of a Framework for the Creation of User Experience Questionnaires , 2019, Int. J. Interact. Multim. Artif. Intell..

[27]  A. Isen,et al.  Positive affect and decision making. , 1993 .

[28]  Joost C. F. de Winter,et al.  Workload assessment for mental arithmetic tasks using the task-evoked pupillary response , 2015, PeerJ Prepr..

[29]  Martin Schrepp,et al.  Eine modulare Erweiterung des User Experience Questionnaire , 2019, UP.

[30]  K. Teigen.  Yerkes-Dodson: A Law for all Seasons , 1994 .

[31]  H. Kaiser,et al.  Little Jiffy, Mark Iv , 1974 .

[32]  N. Tractinsky,et al.  What is beautiful is usable , 2000, Interact. Comput..

[33]  J. W. Senders,et al.  HUMAN ERROR IN ROAD ACCIDENTS , 1999 .

[34]  Matthias Peissner,et al.  Voice User Interface Design , 2004, UP.

[35]  E. Berscheid,et al.  What is beautiful is good. , 1972, Journal of personality and social psychology.

[36]  N. Schwarz,et al.  Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver's Processing Experience? , 2004, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

[37]  Scott A. Shappell,et al.  A Human Error Analysis of Commercial Aviation Accidents Using the Human Factors Analysis and Classification System (HFACS) , 2001 .

[38]  David Chek Ling Ngo,et al.  Formalising guidelines for the design of screen layouts , 2000 .

[39]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[40]  Morten Moshagen,et al.  A short version of the visual aesthetics of websites inventory , 2013 .

[41]  Noam Tractinsky,et al.  Assessing dimensions of perceived visual aesthetics of web sites , 2004 .

[42]  Charlotte Sennersten,et al.  Modeling cognitive load and physiological arousal through pupil diameter and heart rate , 2018, Multimedia Tools and Applications.

[43]  Siyuan Chen,et al.  Using Task-Induced Pupil Diameter and Blink Rate to Infer Cognitive Load , 2014, Hum. Comput. Interact..

[44]  Marc Hassenzahl,et al.  User experience - a research agenda , 2006, Behav. Inf. Technol..

[45]  D. Norman.  Emotional design : why we love (or hate) everyday things , 2004 .

[46]  Robert Graham,et al.  Towards a tool for the Subjective Assessment of Speech System Interfaces (SASSI) , 2000, Natural Language Engineering.

[47]  G. T. Ford,et al.  Inferential Beliefs in Consumer Evaluations: An Assessment of Alternative Processing Strategies , 1987 .

[48]  Masaaki Kurosu,et al.  Apparent usability vs. inherent usability: experimental analysis on the determinants of the apparent usability , 1995, CHI 95 Conference Companion.

[49]  Matteo D'Amore,et al.  Experimental Framework for Simulators to Study Driver Cognitive Distraction: Brake Reaction Time in Different Levels of Arousal , 2016 .

[50]  Dominique Winter,et al.  Welche UX Faktoren sind für mein Produkt wichtig? , 2017, Usability Professionals.

[51]  David L. Strayer,et al.  80 MPH and out-of-the-loop: Effects of real-world semi-automated driving on driver workload and arousal , 2018, Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

[52]  Ying Gao,et al.  Affective Assessment by Digital Processing of the Pupil Diameter , 2013, IEEE Transactions on Affective Computing.

[53]  Jörg Thomaschewski,et al.  Measuring User Experience Quality of Voice Assistants Voice Communication Scales for the UEQ+Framework : Voice Communication Scales for the UEQ+ Framework , 2020, 2020 15th Iberian Conference on Information Systems and Technologies (CISTI).

[54]  Henning Brau,et al.  Erweiterung des UEQ um die Dimensionen Akustik und Haptik , 2017, Usability Professionals.