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Personality in speech: assessment and automatic classification
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 th...
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Lenguaje: | eng |
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Springer
2015
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Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-09516-5 http://cds.cern.ch/record/1968678 |
_version_ | 1780944667133607936 |
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author | Polzehl, Tim |
author_facet | Polzehl, Tim |
author_sort | Polzehl, Tim |
collection | CERN |
description | 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. |
id | cern-1968678 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2015 |
publisher | Springer |
record_format | invenio |
spelling | cern-19686782021-04-21T20:50:15Zdoi:10.1007/978-3-319-09516-5http://cds.cern.ch/record/1968678engPolzehl, TimPersonality in speech: assessment and automatic classificationEngineeringThis 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.Springeroai:cds.cern.ch:19686782015 |
spellingShingle | Engineering Polzehl, Tim Personality in speech: assessment and automatic classification |
title | Personality in speech: assessment and automatic classification |
title_full | Personality in speech: assessment and automatic classification |
title_fullStr | Personality in speech: assessment and automatic classification |
title_full_unstemmed | Personality in speech: assessment and automatic classification |
title_short | Personality in speech: assessment and automatic classification |
title_sort | personality in speech: assessment and automatic classification |
topic | Engineering |
url | https://dx.doi.org/10.1007/978-3-319-09516-5 http://cds.cern.ch/record/1968678 |
work_keys_str_mv | AT polzehltim personalityinspeechassessmentandautomaticclassification |