Toward a social signaling framework : activity and emphasis in speech

Language is not the only form of verbal communication. Loudness, pitch, speaking rate, and other non-linguistic speech features are crucial aspects of human spoken interaction. In this thesis, we separate these speech features into two categories -- vocal Activity and vocal Emphasis -- and propose a framework for classifying high-level social behavior according to those metrics. We present experiments showing that non-linguistic speech analysis alone can account for appreciable portions of social phenomena. We report statistically significant results in measuring the persuasiveness of pitches, the effectiveness of customer service representatives, and the severity of depression. Effect sizes of these studies explain up to 60% of the sample variances and yield binary decision accuracies nearing 90%.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Stoltzman, William T

Advisor dc:contributor.advisor

• Alex P. Pentland.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/41537

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/41537