OKADA, Shogo Associate Professor
Information Science, Human Information Science, Research Centre for Interpretable AI, Research Center for Cohabitative-AI×Design (Research Core), Research Center for Biological Function and Sensory Information, Research Center for Vision Oriented Society Design
◆Degrees
B.S. from Yokohama National University (2003), M.S. from Tokyo Institute of Technology (2005), Ph.D from Tokyo Institute of Technology (2008)
◆Professional Experience
2021 - : Seikei University , Visiting researcher
2018 - : 理化学研究所 , 革新知能統合センター , 客員研究員
2017 - : Japan Advanced Institute of Science and Technology , School of Information Science , Associate Professor
2014 - : Visting fuculty at IDIAP research institute
2011 - : Assistant Professor at Tokyo Institute of Technology
2008 - : Project Assistant Professor at Kyoto University
◆Specialties
Human interfaces and interactions, Intelligent informatics
◆Research Keywords
Data mining, Machine learning, Human dynamics, Multimodal Interaction, Social Signal Processing
◆Research Interests
Human dynamics and social signal processing based on multimodal machine learning and data mining, and it's application for communicative robot/ agen.
(1)Multimodal Interaction Modeling: Face to face conversation is a fundamental communication method for information sharing, decision making and consensus building. It has various kind of types: casual talking with friends, business meeting, negotiation, counseling, and so on. People send not only verbal information, but also nonverbal information each other. Their role in conversation, attitude (e.g. passive, active, cooperative), intention (e.g. agree), and emotional state sometimes can be observed from their multimodal (verbal and nonverbal) signals called social signals [A.Vinciarelli et al 2009]. Conversational states such as lively discussion and to be silent can be observed by fusing social signals of all members. My researches focus on building computational model of multimodal social signals (speech, gaze, gesture and so on.) by using speech signal processing, image processing, motion sensor processing and pattern recognition techniques. My research question is how these social signal patterns influence high level output and tacit knowledge such as output after consensus building, communication skills and explanation skills. These modeling techniques can be also used to develop a sensing module for conversational robots/agents. (2) Human Dynamics Modeling: Recent progress in developing sensors: location sensors, for monitoring human motion and activity has become available for analyzing longitudinal human activity and it’s dynamics in real environment. A research focuses on analyzing of office worker’s activity from sensor environment set in office. Another research focuses on analyzing of driver’s behaviors (brake patterns, how to press the accelerator or the brakes) from sensor environment equipped in cars. (3) Machine Learning and Data Mining: Phenomenon of multimodal interaction and human dynamics are observed as continuous multi-dimensional time-series data from multiple sensors. Machine learning techniques are important to build recognition model from these multidimensional time-series data set. It is difficult to define Social signal patterns and typical activity patterns in office and represent features of it. To discover the structure of these patterns, Data mining algorithm are also useful. In particular, we focus on developing time-series clustering, multidimensional motif discovery and change point detection algorithm and applied to find various patterns and structure of data

■Publications

◆Published Papers
Adversarial Domain Generalized Transformer for Cross-Corpus Speech Emotion Recognition
Yuan Gao, Longbiao Wang, Jiaxing Liu, Jianwu Dang, Shogo Okada
IEEE Transactions on Affective Computing, -, 2024
Multimodal Transfer Learning for Oral Presentation Assessment.
Su Shwe Yi Tun, Shogo Okada, Hung-Hsuan Huang, Chee Wee Leong
IEEE Access, 11, 84013-84026, 2023
A Ranking Model for Evaluation of Conversation Partners Based on Rapport Levels.
Takato Hayashi, Candy Olivia Mawalim, Ryo Ishii, Akira Morikawa, Atsushi Fukayama, Takao Nakamura, Shogo Okada
IEEE Access, 11, 73024-73035, 2023
Adaptive Interview Strategy Based on Interviewees Speaking Willingness Recognition for Interview Robots
Fuminori Nagasawa, Shogo Okada, Takuya Ishihara, Katsumi Nitta
IEEE Transactions on Affective Computing, 1-17, 2023
Detecting Change Talk in Motivational Interviewing using Verbal and Facial Information.
Yukiko I. Nakano, Eri Hirose, Tatsuya Sakato, Shogo Okada, Jean-Claude Martin
ICMI, 5-14, 2022
◆Misc
Analysis of Role of Multimodal Information and Physiological Signals in Self-Reported and Third-Party Sentiment Estimation
堅田俊, 岡田将吾, 駒谷和範
電子情報通信学会技術研究報告(Web), 122, 349(HCS2022 55-75), -, 2023
Analysis of the robustness of modulation spectral features to noise reverberation in speech emotion recognition.
GUO Taiyang, LI Sixia, 鵜木祐史, 岡田将吾
日本音響学会研究発表会講演論文集(CD-ROM), 2023, -, 2023
Postoperative Complications of Primary Breast Reconstruction by Tissue-expander or Implant for Breast Cancer
甲斐あずさ, 舛本法生, 藤本睦, 鈴木江梨, 小林美恵, 笹田伸介, 恵美純子, 角舎学行, 佐々木彩乃, 永松将吾, 岡田守人
乳癌の臨床, 38, 3, -, 2023
Ranking Conversations based on Rapport in First Meeting Conversations and Friend Conversations
林貴斗, 基村竜晟, 石井亮, 二瓶芙巳雄, 深山篤, 岡田将吾
人工知能学会言語・音声理解と対話処理研究会資料, 98, -, 2023
Analyzing Job Interview Responses with PREP-Based Discourse Structure Annotations
前田雄之介, 井之上直也, 井之上直也, 岡田将吾
人工知能学会全国大会論文集(Web), 37th, -, 2023
◆Conference Activities & Talks
マルチモーダル対話データの収集と興味判定アノテーションの分析
人工知能学会 音声・言語理解と対話処理研究会(SLUD)第81回研究会, 2017
グループディスカッション参加者の役割に基づいた会話状況とコミュニ ケーション能力の分析
人工知能学会全国大会2017, 2017
ユーザーの態度推定に基づき適応的なインタビューを行うロボット対話 システムの開発
人工知能学会全国大会2017 音声・言語理解と対話処理研究会(SLUD)第81回研究会, 2017
マルチモーダル情報に基づくインタビューにおける重要シーンの推定
IEICE HCGシンポジウム2017, 2017

■Teaching Experience

Analysis of Information Science, 機械学習

■Contributions to  Society

◆Academic Society Affiliations
ACM, THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS, THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE, IEEE
◆Academic Contribution
ACM International Conference on Multimodal Interaction (ICMI 2016) , Organizing CommitteeLocal Organization ChairShogo Okada (Tokyo Institute of Technology, Japan) , 2016 - 2016 , 東京 お台場開催,マルチモーダルインタラクションのトップカンファレンス

■Academic  Awards

・ Outstanding performance award(2位) , MIYAMA, 三山 有, 岡田 将吾 , 対話ロボットコンペティション2022 , 2022
・ Best Paper Runner-up Award , Yukiko Nakano, Eri Hirose, Tatsuya Sakato, Shogo Okada, Jean-Claude MARTIN , ACM International Conference on Multimodal Interaction (2022) , 2022
・ 物質・デバイス共同研究賞 , 岡田将吾, 駒谷和範 , 物質 デバイス領域共同研究拠点 , 2022