People hesitate more, talk less to virtual interviewers than to human interviewers

In a series of screening interviews for psychological distress, conducted separately by a human interviewer and by an animated virtual character controlled by a human, participants talked substantially less and produced twice as many filled pauses when talking to the virtual character. This contrasts with earlier findings, where people were less disfluent when talking to a computer dialogue system. The results suggest that the characteristics of computer-directed speech vary depending on the type of dialogue system used.

[1]  J. Cassell,et al.  Towards a model of technology and literacy development: Story listening systems , 2004 .

[2]  Martin Corley,et al.  Hesitation Disfluencies in Spontaneous Speech: The Meaning of um , 2008, Lang. Linguistics Compass.

[3]  J. Bavelas,et al.  Listeners as co-narrators. , 2000, Journal of personality and social psychology.

[4]  E. Blanchard,et al.  Psychometric properties of the PTSD Checklist (PCL). , 1996, Behaviour research and therapy.

[5]  Sharon L. Oviatt,et al.  Multimodal interfaces for dynamic interactive maps , 1996, CHI.

[6]  Lee Sproull,et al.  When the Interface Is a Face , 1996, Hum. Comput. Interact..

[7]  Sharon L. Oviatt,et al.  Predicting spoken disfluencies during human-computer interaction , 1995, Comput. Speech Lang..

[8]  Shrikanth S. Narayanan,et al.  Comparison of child-human and child-computer interactions based on manual annotations , 2009, WOCCI '09.

[9]  Arne Jönsson,et al.  Talking to a Computer Is Not like Talking to Your Best Friend , 1988, SCAI.

[10]  Kallirroi Georgila,et al.  Verbal indicators of psychological distress in interactive dialogue with a virtual human , 2013, SIGDIAL Conference.

[11]  Stacy Marsella,et al.  A Virtual Human Dialogue Model for Non-Team Interaction , 2008 .

[12]  J. Pennebaker,et al.  Language use of depressed and depression-vulnerable college students , 2004 .

[13]  Shrikanth S. Narayanan,et al.  Automatic Detection of Disfluency Boundaries in Spontaneous Speech of Children Using Audio–Visual Information , 2009, IEEE Transactions on Audio, Speech, and Language Processing.

[14]  S. Brennan,et al.  Disfluency Rates in Conversation: Effects of Age, Relationship, Topic, Role, and Gender , 2001, Language and speech.

[15]  Justine Cassell,et al.  Modeling culturally authentic style shifting with virtual peers , 2009, ICMI-MLMI '09.

[16]  Sharon L. Oviatt Talking to thimble jellies: children²s conversational speech with animated characters , 2000, INTERSPEECH.

[17]  R. Spitzer,et al.  The PHQ-9: A new depression diagnostic and severity measure , 2002 .

[18]  Stefan Kopp,et al.  A Conversational Agent as Museum Guide - Design and Evaluation of a Real-World Application , 2005, IVA.

[19]  Elizabeth Shriberg DISFLUENCIES IN SWITCHBOARD , 1996 .

[20]  M. Pickering,et al.  Linguistic alignment between people and computers , 2010 .

[21]  Hennie Brugman,et al.  Annotating Multi-media/Multi-modal Resources with ELAN , 2004, LREC.

[22]  J. Pennebaker,et al.  Word Use in the Poetry of Suicidal and Nonsuicidal Poets , 2001, Psychosomatic medicine.

[23]  Albert A. Rizzo,et al.  Automatic behavior descriptors for psychological disorder analysis , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).