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Personality in speechassessment and ...

Polzehl, Tim.

Personality in speechassessment and automatic classification /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Personality in speechby Tim Polzehl.
Reminder of title:	assessment and automatic classification /
Author:	Polzehl, Tim.
Published:	Cham :Springer International Publishing :2015.
Description:	xiv, 176 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Natural language processing (Computer science)
Online resource:	http://dx.doi.org/10.1007/978-3-319-09516-5
ISBN:	9783319095165 (electronic bk.)

Personality in speechassessment and automatic classification /
Polzehl, Tim.

Personality in speechassessment and automatic classification /[electronic resource] :by Tim Polzehl. - Cham :Springer International Publishing :2015. - xiv, 176 p. :ill. (some col.), digital ;24 cm. - T-Labs series in telecommunication services,2192-2810. - T-Labs series in telecommunication services..

This work combines interdisciplinary knowledge and experience from research fields of psychology, linguistics, audio-processing, machine learning, and computer science. The work systematically explores a novel research topic devoted to automated modeling of personality expression from speech. For this aim, it introduces a novel personality assessment questionnaire and presents the results of extensive labeling sessions to annotate the speech data with personality assessments. It provides estimates of the Big 5 personality traits, i.e. openness, conscientiousness, extroversion, agreeableness, and neuroticism. Based on a database built on the questionnaire, the book presents models to tell apart different personality types or classes from speech automatically.

ISBN: 9783319095165 (electronic bk.)

Standard No.: 10.1007/978-3-319-09516-5doiSubjects--Topical Terms:

200539
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

Personality in speechassessment and automatic classification /
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520 $a This work combines interdisciplinary knowledge and experience from research fields of psychology, linguistics, audio-processing, machine learning, and computer science. The work systematically explores a novel research topic devoted to automated modeling of personality expression from speech. For this aim, it introduces a novel personality assessment questionnaire and presents the results of extensive labeling sessions to annotate the speech data with personality assessments. It provides estimates of the Big 5 personality traits, i.e. openness, conscientiousness, extroversion, agreeableness, and neuroticism. Based on a database built on the questionnaire, the book presents models to tell apart different personality types or classes from speech automatically.
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