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2021 | OriginalPaper | Chapter

Emotion Estimating Method by Using Voice and Facial Expression Parameters

Author : Kimihiro Yamanaka

Published in: Computer Information Systems and Industrial Management

Publisher: Springer International Publishing

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Abstract

This study aimed to propose a method of emotion estimation using facial expression and speech features for machine learning with fewer parameters than in previous studies. In the experiment, emotions were evoked in participants by displaying emotion-activation movies. Facial expressions and voice parameters were then extracted. These parameters were used to estimate emotions by machine learning. In machine learning, six types of learning were performed by combining objective variables and explanatory variables. It was shown that classification can be performed with an accuracy of 93.3% when only voice parameters are used in two-category classification, such as positive and negative.

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Metadata
Title
Emotion Estimating Method by Using Voice and Facial Expression Parameters
Author
Kimihiro Yamanaka
Copyright Year
2021
Book
Computer Information Systems and Industrial Management

Print ISBN: 978-3-030-84339-7

Electronic ISBN: 978-3-030-84340-3

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-84340-3_18

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