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Personality in Speech electronic resource Assessment and Automatic Classification / by Tim Polzehl.

By: Polzehl, Tim [author.]Contributor(s): SpringerLink (Online service)Material type: TextTextSeries: T-Labs Series in Telecommunication ServicesPublication details: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XIV, 176 p. 39 illus., 34 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319095165Subject(s): engineering | User interfaces (Computer systems) | Computational linguistics | PERSONality | social psychology | Engineering | Signal, Image and Speech Processing | Personality and Social Psychology | User Interfaces and Human Computer Interaction | Computational LinguisticsDDC classification: 621.382 LOC classification: TK5102.9TA1637-1638TK7882.S65Online resources: Click here to access online In: Springer eBooksSummary: 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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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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