The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
사회 기술 훈련(SST)은 더 나은 일상 생활을 구축하기 위해 개인의 사회적 기술을 향상시키기 위해 수년 동안 사용되어 왔습니다. 인간이 수행하는 SST에서 사회적 기술 수준은 일반적으로 트레이너가 실시하는 구두 인터뷰를 통해 평가됩니다. 이러한 평가는 정신의학적 지식과 전문적인 경험을 바탕으로 이루어지지만, 그 질은 트레이너의 능력에 따라 달라집니다. 따라서 이러한 평가를 표준화하려면 정량화 가능한 지표가 필요합니다. 이러한 요구를 충족시키기 위해 사회적 반응 척도(SRS-2) 제2판은 실증적 연구 작업을 통해 광범위하게 테스트되고 표준화되었기 때문에 실행 가능한 솔루션을 제공합니다. 이 논문에서는 SRS-0.76를 기반으로 개인의 사회적 기술 수준을 평가하는 자동화된 방법의 개발에 대해 설명합니다. BERT 기반 특징을 포함한 다중 모달 특징을 사용하고 특징 선택을 사용하면서 XNUMX Pearson 상관 계수로 점수 추정을 수행합니다. 또한, 주관적 평가를 통해 BERT 기반 기능의 언어학적 측면을 살펴봅니다. 결과적으로 BERT 기반 기능은 인간의 주관적 유창성 점수, 적절한 단어 선택 및 이해 가능한 음성 구조와 강한 음의 상관 관계를 보여줍니다.
Takeshi SAGA
Nara Institute of Science and Technology
Hiroki TANAKA
Nara Institute of Science and Technology
Hidemi IWASAKA
Nara Medical University
Satoshi NAKAMURA
Nara Institute of Science and Technology
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Takeshi SAGA, Hiroki TANAKA, Hidemi IWASAKA, Satoshi NAKAMURA, "Multimodal Prediction of Social Responsiveness Score with BERT-Based Text Features" in IEICE TRANSACTIONS on Information,
vol. E105-D, no. 3, pp. 578-586, March 2022, doi: 10.1587/transinf.2021HCP0009.
Abstract: Social Skills Training (SST) has been used for years to improve individuals' social skills toward building a better daily life. In SST carried out by humans, the social skills level is usually evaluated through a verbal interview conducted by the trainer. Although this evaluation is based on psychiatric knowledge and professional experience, its quality depends on the trainer's capabilities. Therefore, to standardize such evaluations, quantifiable metrics are required. To meet this need, the second edition of the Social Responsiveness Scale (SRS-2) offers a viable solution because it has been extensively tested and standardized by empirical research works. This paper describes the development of an automated method to evaluate a person's social skills level based on SRS-2. We use multimodal features, including BERT-based features, and perform score estimation with a 0.76 Pearson correlation coefficient while using feature selection. In addition, we examine the linguistic aspects of BERT-based features through subjective evaluations. Consequently, the BERT-based features show a strong negative correlation with human subjective scores of fluency, appropriate word choice, and understandable speech structure.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021HCP0009/_p
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@ARTICLE{e105-d_3_578,
author={Takeshi SAGA, Hiroki TANAKA, Hidemi IWASAKA, Satoshi NAKAMURA, },
journal={IEICE TRANSACTIONS on Information},
title={Multimodal Prediction of Social Responsiveness Score with BERT-Based Text Features},
year={2022},
volume={E105-D},
number={3},
pages={578-586},
abstract={Social Skills Training (SST) has been used for years to improve individuals' social skills toward building a better daily life. In SST carried out by humans, the social skills level is usually evaluated through a verbal interview conducted by the trainer. Although this evaluation is based on psychiatric knowledge and professional experience, its quality depends on the trainer's capabilities. Therefore, to standardize such evaluations, quantifiable metrics are required. To meet this need, the second edition of the Social Responsiveness Scale (SRS-2) offers a viable solution because it has been extensively tested and standardized by empirical research works. This paper describes the development of an automated method to evaluate a person's social skills level based on SRS-2. We use multimodal features, including BERT-based features, and perform score estimation with a 0.76 Pearson correlation coefficient while using feature selection. In addition, we examine the linguistic aspects of BERT-based features through subjective evaluations. Consequently, the BERT-based features show a strong negative correlation with human subjective scores of fluency, appropriate word choice, and understandable speech structure.},
keywords={},
doi={10.1587/transinf.2021HCP0009},
ISSN={1745-1361},
month={March},}
부
TY - JOUR
TI - Multimodal Prediction of Social Responsiveness Score with BERT-Based Text Features
T2 - IEICE TRANSACTIONS on Information
SP - 578
EP - 586
AU - Takeshi SAGA
AU - Hiroki TANAKA
AU - Hidemi IWASAKA
AU - Satoshi NAKAMURA
PY - 2022
DO - 10.1587/transinf.2021HCP0009
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E105-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2022
AB - Social Skills Training (SST) has been used for years to improve individuals' social skills toward building a better daily life. In SST carried out by humans, the social skills level is usually evaluated through a verbal interview conducted by the trainer. Although this evaluation is based on psychiatric knowledge and professional experience, its quality depends on the trainer's capabilities. Therefore, to standardize such evaluations, quantifiable metrics are required. To meet this need, the second edition of the Social Responsiveness Scale (SRS-2) offers a viable solution because it has been extensively tested and standardized by empirical research works. This paper describes the development of an automated method to evaluate a person's social skills level based on SRS-2. We use multimodal features, including BERT-based features, and perform score estimation with a 0.76 Pearson correlation coefficient while using feature selection. In addition, we examine the linguistic aspects of BERT-based features through subjective evaluations. Consequently, the BERT-based features show a strong negative correlation with human subjective scores of fluency, appropriate word choice, and understandable speech structure.
ER -