Automatic Emoticons Insertion System Based on Acoustic Information of User Voice: 1st Report on Data Model for Emotion Estimation Using Machine Learning

Ryo Senuma, Sho Yokota, Akihiro Matsumoto, Daisuke Chugo, Satoshi Muramatsu, Hiroshi Hashimoto

2023

Abstract

In social media, text information has a problem that it is difficult to convey the nuances and emotions to the other people. Moreover, manual texting is a time consuming task. Therefore, this research proposes a system that creates text information by voice input from the acoustic information, and automatically insert emoticons matching the user’s emotion. The proposed system is employed based on the eight basic emotions of Plutchik’s Wheel of Emotions. Two types of data: natural utterances voice and acting voice was applied to the SVM (Support Vector Machine) method in the experiment to estimate emotions. The result shows that the accuracy of natural utterances voice and acting voice are 30% and 70%, respectively.

Paper Citation

in Harvard Style

Senuma R., Yokota S., Matsumoto A., Chugo D., Muramatsu S. and Hashimoto H. (2023). Automatic Emoticons Insertion System Based on Acoustic Information of User Voice: 1st Report on Data Model for Emotion Estimation Using Machine Learning. In Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: NCTA; ISBN 978-989-758-674-3, SciTePress, pages 548-554. DOI: 10.5220/0012237900003595

in Bibtex Style

@conference{ncta23,
author={Ryo Senuma and Sho Yokota and Akihiro Matsumoto and Daisuke Chugo and Satoshi Muramatsu and Hiroshi Hashimoto},
title={Automatic Emoticons Insertion System Based on Acoustic Information of User Voice: 1st Report on Data Model for Emotion Estimation Using Machine Learning},
booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: NCTA},
year={2023},
pages={548-554},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012237900003595},
isbn={978-989-758-674-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: NCTA
TI - Automatic Emoticons Insertion System Based on Acoustic Information of User Voice: 1st Report on Data Model for Emotion Estimation Using Machine Learning
SN - 978-989-758-674-3
AU - Senuma R.
AU - Yokota S.
AU - Matsumoto A.
AU - Chugo D.
AU - Muramatsu S.
AU - Hashimoto H.
PY - 2023
SP - 548
EP - 554
DO - 10.5220/0012237900003595
PB - SciTePress