Discussion-skill Analytics with Acoustic, Linguistic and Psychophysiological Data

Katashi Nagao, Kosuke Okamoto, Shimeng Peng, Shigeki Ohira

2019

Abstract

In this paper, we propose a system for improving the discussion skills of participants in a meeting by automatically evaluating statements in the meeting and effectively feeding back the results of the evaluation to them. To evaluate the skills automatically, the system uses both acoustic features and linguistic features of statements. It evaluates the way a person speaks, such as their “voice size,” on the basis of the acoustic features, and it also evaluates the contents of a statement, such as the “consistency of context,” on the basis of linguistic features. These features can be obtained from meeting minutes. Since it is difficult to evaluate the semantic contents of statements such as the “consistency of context,” we build a machine learning model that uses the features of minutes such as speaker attributes and the relationship of statements. In addition, we argue that participants’ heart rate (HR) data can be used to effectively evaluate their cognitive performance, specifically the performance in a discussion that consists of several Q&A segments (question-and-answer pairs). We collect HR data during a discussion in real time and generate machine-learning models for evaluation. We confirmed that the proposed method is effective for evaluating the discussion skills of meeting participants.

Paper Citation

in Harvard Style

Nagao K., Okamoto K., Peng S. and Ohira S. (2019). Discussion-skill Analytics with Acoustic, Linguistic and Psychophysiological Data. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR; ISBN 978-989-758-382-7, SciTePress, pages 409-418. DOI: 10.5220/0008332304090418

in Bibtex Style

@conference{kdir19,
author={Katashi Nagao and Kosuke Okamoto and Shimeng Peng and Shigeki Ohira},
title={Discussion-skill Analytics with Acoustic, Linguistic and Psychophysiological Data},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR},
year={2019},
pages={409-418},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008332304090418},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR
TI - Discussion-skill Analytics with Acoustic, Linguistic and Psychophysiological Data
SN - 978-989-758-382-7
AU - Nagao K.
AU - Okamoto K.
AU - Peng S.
AU - Ohira S.
PY - 2019
SP - 409
EP - 418
DO - 10.5220/0008332304090418
PB - SciTePress