Predicting Individual Well-Being in Teamwork Contexts Based on Speech Features

Current methods for assessing individual well-being in team collaboration at the workplace often rely on manually collected surveys. This limits continuous real-world data collection and proactive measures to improve team member workplace satisfaction. We propose a method to automatically derive soc...

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書誌詳細

主要な著者:	Tobias Zeulner, Gerhard Johann Hagerer, Moritz Müller, Ignacio Vazquez, Peter A. Gloor
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-04-01
シリーズ:	Information
主題:	explainable AI multi-modal speaker diarization affective computing social signal processing team collaboration
オンライン･アクセス:	https://www.mdpi.com/2078-2489/15/4/217
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