Towards the detection of social dominance in dialogue

Authors:
Simon F. Worgan;Roger K. Moore
Affiliations:
Speech and Hearing Research Group, Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK;Speech and Hearing Research Group, Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK
Venue:
Speech Communication
Year:
2011

Citing 6
Cited 2

Vocal communication of emotion: a review of research paradigms

Speech Communication - Special issue on speech and emotion
The production and recognition of emotions in speech: features and algorithms

International Journal of Human-Computer Studies - Application of affective computing in human—Computer interaction
PRESENCE: A Human-Inspired Architecture for Speech-Based Human-Machine Interaction

IEEE Transactions on Computers
EmoVoice -- A Framework for Online Recognition of Emotions from Voice

PIT '08 Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems
The contribution of changes in F0 and spectral tilt to increased intelligibility of speech produced in noise

Speech Communication
Virtual rapport

IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents

Characterization of coordination in an imitation task: human evaluation and automatically computable cues

ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Inferring social nature of conversations from words: Experiments on a corpus of everyday telephone conversations

Computer Speech and Language

Quantified Score

Hi-index	0.00

Visualization

Abstract

When developing human-computer conversational systems the complex co-acting processes of human-human dialogue present a significant challenge. Para-linguistic features establish rapport between individuals and direct the conversation in directions that cannot be captured by semantic analysis alone. This paper attempts to address part of this challenge by considering the role of para-linguistic features in establishing and manipulating social dominance. We propose that social dominance can be understood as an interaction affordance, revealing action potentials for each signalling participant, and can be detected as a feature of rapport not of the individual. An analysis of F0 and long-term averaged spectra (LTAS) correlation values for conversational pairs reveals a high degree of accommodation. The nature of this accommodation demonstrates that others will adjust their speech to match the current dominant individual. We conclude by exploring the implications of these results on the role of rapport and outline potential advances for the detection of emotion in speech by encompassing the entirety of pleasure-arousal-dominance emotional space.