| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2024-01-30 |
| タイトル |
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タイトル |
Automatic evaluation-feedback system for automated social skills training |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ |
journal article |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
Saga, Takeshi
田中, 宏季
Matsuda, Yasuhiro
Morimoto, Tsubasa
Uratani, Mitsuhiro
Okazaki, Kosuke
藤本, 雄一郎
中村, 哲
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Social skills training (SST), which is a rehabilitation program for improving daily interpersonal communication, has been used for more than 40 years. Although such training’s demand is increasing, its accessibility is limited due to the lack of experienced trainers. To tackle this issue, automated SST systems have been studied for years. An evaluation-feedback pipeline of social skills is a crucial component of an SST system. Unfortunately, research that considers both the evaluation and feedback parts of automation remains insufficient. In this paper, we collected and analyzed the characteristics of a human?human SST dataset that consisted of 19 healthy controls, 15 schizophreniacs, 16 autism spectrum disorder (ASD) participants, and 276 sessions with score labels of six clinical measures. From our analysis of this dataset, we developed an automated SST evaluation-feedback system under the supervision of professional, experienced SST trainers. We identified their preferred or most acceptable feedback methods by running a user-study on the following conditions: with/without recorded video of the role-plays of users and different amounts of positive and corrective feedback. We confirmed a reasonable performance of our social-skill-score estimation models as our system’s evaluation part with a maximum Spearman’s correlation coefficient of 0.68. For the feedback part, our user-study concluded that people understood more about what aspects they need to improve by watching recorded videos of their own performance. In terms of the amount of feedback, participants most preferred a 2-positive/1-corrective format. Since the average amount of feedback preferred by the participants nearly equaled that from experienced trainers in human?human SSTs, our result suggests the practical future possibilities of an automated evaluation-feedback system that complements SSTs done by professional trainers. |
| 書誌情報 |
en : Scientific Reports
巻 13,
号 1,
発行日 2023-04-26
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| 出版者 |
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出版者 |
Nature Research |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
2045-2322 |
| 出版者版DOI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1038/s41598-023-33703-0 |
| 出版者版URI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
URI |
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関連識別子 |
https://www.nature.com/articles/s41598-023-33703-0 |
| 権利 |
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権利情報Resource |
http://creativecommons.org/licenses/by/4.0/ |
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権利情報 |
c The Author(s) 2023 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| 著者版フラグ |
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出版タイプ |
NA |
