発表

85 entries « ‹ 1 of 2 › »

2025

Shota Mochizuki, Sanae Yamashita, Kenya Hoshimure, Jun Baba, Tomonori Kubota, Kohei Ogawa, Ryuichiro Higashinaka

Anomaly Detection in Human-Robot Interaction Using Multimodal Models Constructed from In-the-Wild Interactions Proceedings Article Forthcoming

In: 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Forthcoming.

Yuki Zenimoto, Mariko Yoshida, Ryo Hori, Mayu Urata, Aiko Inoue, Takahiro Hayashi, Ryuichiro Higashinaka

Automated Administration of Questionnaires during Casual Conversation using Question-Guiding Dialogue System Proceedings Article Forthcoming

In: The 29th Workshop on the Semantics and Pragmatics of Dialogue, Forthcoming.

Taro Tsuda, Sanae Yamashita, Koji Inoue, Tatsuya Kawahara, Ryuichiro Higashinaka

Constructing a Multi-Party Conversational Corpus Focusing on Interlocutor Relationships Proceedings Article Forthcoming

In: The 29th Workshop on the Semantics and Pragmatics of Dialogue, Forthcoming.

Ao Guo, Shota Mochizuki, Sanae Yamashita, Saya Nikaido, Tomoko Isomura, Ryuichiro Higashinaka

Exploring Factors Influencing Hospitality in Mobile Robot Guidance: A Wizard-of-Oz Study with a Teleoperated Humanoid Robot Proceedings Article Forthcoming

In: Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL) , Forthcoming.

Jingjing Jiang, Ao Guo, Ryuichiro Higashinaka

Integrating Physiological, Speech, and Textual Information Toward Real-Time Recognition of Emotional Valence in Dialogue Proceedings Article Forthcoming

In: Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL) , Forthcoming.

Atsumoto Ohashi, Shinya Iizuka, Jingjing Jiang, Ryuichiro Higashinaka

Towards a Japanese Full-duplex Spoken Dialogue System Proceedings Article Forthcoming

In: The 26th Interspeech Conference (INTERSPEECH 2025), Forthcoming.

Ao Guo, Atsumoto Ohashi, Ryu Hirai, Yuya Chiba, Yuiko Tsunomori, Ryuichiro Higashinaka

User Personality and its Influence on the Performance of Pipeline and End-to-end Task-oriented Dialogue Systems Journal Article

In: Scientific Reports , vol. 15, no. 1, pp. 20745-20763, 2025, ISBN: 2045-2322.

Abstract | Links | BibTeX

@article{guo-sr-2025,

title = {User Personality and its Influence on the Performance of Pipeline and End-to-end Task-oriented Dialogue Systems},

author = {Ao Guo, Atsumoto Ohashi, Ryu Hirai, Yuya Chiba, Yuiko Tsunomori, Ryuichiro Higashinaka},

url = {https://doi.org/10.1038/s41598-025-07101-7},

doi = {10.1038/s41598-025-07101-7},

isbn = {2045-2322},

year  = {2025},

date = {2025-07-01},

urldate = {2025-07-01},

journal = {Scientific Reports },

volume = {15},

number = {1},

pages = {20745-20763},

abstract = {A task-oriented dialogue system with adaptability to user personality could potentially improve dialogue task performance in terms of task success and user satisfaction. In practice, however, the implementation of such a dialogue system would be challenging because of our limited understanding of how user personality influences dialogue task performance. Understanding these influences is essential for developing dialogue strategies that adapt to user personalities, allowing a dialogue system to cater to different users and thereby improve task performance. To examine these influences, we collected data by enrolling crowd-sourced participants to answer personality questionnaires and then chat with a dialogue system to accomplish assigned dialogue tasks. The dialogue tasks were designed using the MultiWOZ dataset, which covers dialogues between a clerk bot and a customer in the context of tourist information access. To clarify the general influence of personality on dialogue task performance across different dialogue systems, we conducted a comparative analysis using both a pipeline system and an end-to-end (E2E) system. We first explored the correlation among user personality, user dialogue behavior, and dialogue task performance through correlation analysis. The results indicate a weak correlation between user personality and dialogue task performance, along with stronger correlations between dialogue behavior with both user personality and dialogue task performance. On the basis of the results of the correlation analysis, we then used Structural Equation Modeling (SEM) to analyze the relationships between user personality and dialogue task performance, using user dialogue behavior as an intermediate variable. The constructed SEM models showed good fit indices. Our results indicate that neutral perceptual sensitivity (which measures a user’s sensitivity to external stimuli) and emotional management skill (which measures a user’s ability to regulate his/her emotional reactions to situations) have significant influences on his/her dialogue task performance across different dialogue systems. In addition, our findings reveal that personality traits, such as extraversion and conscientiousness, influence dialogue task performance, although such influences may be subject to context-specific variability such as dialogue task design, dialogue domain (MultiWOZ), and system architecture (pipeline).



},

keywords = {},

pubstate = {published},

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A task-oriented dialogue system with adaptability to user personality could potentially improve dialogue task performance in terms of task success and user satisfaction. In practice, however, the implementation of such a dialogue system would be challenging because of our limited understanding of how user personality influences dialogue task performance. Understanding these influences is essential for developing dialogue strategies that adapt to user personalities, allowing a dialogue system to cater to different users and thereby improve task performance. To examine these influences, we collected data by enrolling crowd-sourced participants to answer personality questionnaires and then chat with a dialogue system to accomplish assigned dialogue tasks. The dialogue tasks were designed using the MultiWOZ dataset, which covers dialogues between a clerk bot and a customer in the context of tourist information access. To clarify the general influence of personality on dialogue task performance across different dialogue systems, we conducted a comparative analysis using both a pipeline system and an end-to-end (E2E) system. We first explored the correlation among user personality, user dialogue behavior, and dialogue task performance through correlation analysis. The results indicate a weak correlation between user personality and dialogue task performance, along with stronger correlations between dialogue behavior with both user personality and dialogue task performance. On the basis of the results of the correlation analysis, we then used Structural Equation Modeling (SEM) to analyze the relationships between user personality and dialogue task performance, using user dialogue behavior as an intermediate variable. The constructed SEM models showed good fit indices. Our results indicate that neutral perceptual sensitivity (which measures a user’s sensitivity to external stimuli) and emotional management skill (which measures a user’s ability to regulate his/her emotional reactions to situations) have significant influences on his/her dialogue task performance across different dialogue systems. In addition, our findings reveal that personality traits, such as extraversion and conscientiousness, influence dialogue task performance, although such influences may be subject to context-specific variability such as dialogue task design, dialogue domain (MultiWOZ), and system architecture (pipeline).

姜菁菁，郭傲，東中竜一郎

対話中の生体信号を用いた時系列モデルによる感情分類 Proceedings Article

In: 人工知能学会全国大会論文集第 39 回全国大会 (2025), pp. 3Win5-55, 2025.

植竹眞斗, 窪田智徳, 岩﨑雅矢, 望月翔太, 山下紗苗, 郭傲, 星牟禮健也, 馬場惇, 東中竜一郎, 佐藤理史, 小川浩平

操作者と操作対象ロボットとの対話により長時間操作の退屈感を低減する遠隔操作システムの開発 Proceedings Article

In: 人工知能学会全国大会論文集第 39 回全国大会 (2025), pp. 3Q6GS802–3Q6GS802, 2025.

藤枝佑喜, 東中竜一郎

ホワイトボードを使用した共同作業タスクにおける対話の収集と分析 Proceedings Article

In: 人工知能学会全国大会論文集第 39 回全国大会 (2025), pp. 3Win5-33, 2025.

大橋厚元, 東中竜一郎

タスク指向対話システムにおける全モジュールの後処理の同時最適化 Proceedings Article

In: 人工知能学会全国大会論文集第 39 回全国大会 (2025), pp. 3R1OS45–3R1OS45, 2025.

Mariko Yoshida, Ryo Hori, Yuki Zenimoto, Mayu Urata, Mamoru Endo, Takami Yasuda, Aiko Inoue, Takahiro Hayashi, Ryuichiro Higashinaka

Examining Older Adults’ Motivation for Interacting with Health-Monitoring Conversational Systems Through Field Trials Proceedings Article

In: Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology, pp. 103-114, 2025.

Abstract | Links | BibTeX

Ryuichiro Higashinaka, Tetsuro Takahashi, Shinya Iizuka, Sota Horiuchi, Michimasa Inaba, Zhiyang Qi, Yuta Sasaki, Kotaro Funakoshi, Shoji Moriya, Shiki Sato, Takashi Minato, Kurima Sakai, Tomo Funayama, Masato Komuro, Hiroyuki Nishikawa, Ryosaku Makino, Hirofumi Kikuchi, Mayumi Usami

DSLCMM: A Multimodal Human-Machine Dialogue Corpus Built through Competitions Proceedings Article

In: Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology, pp. 277-283, 2025.

Abstract | Links | BibTeX

山下紗苗, 東中竜一郎

オペレータが交換したメモの分析に基づく円滑な対話の引継ぎに有用な情報の明確化 Journal Article

In: ヒューマンインタフェース学会論文誌, vol. 27, iss. 2, pp. 113–124, 2025.

佐藤友紀, 高道慎之介, 東中竜一郎

YouTube 上の対話動画に基づく音声対話データセットの構築 Proceedings Article

In: 日本音響学会第153回（2025年春季）研究発表会講演論文集, 2025.

銭本友樹, 吉田麻里子, 堀涼, 浦田真由, 井上愛子, 林尊弘, 東中竜一郎

質問誘導に基づくアンケート対話システムの開発 Proceedings Article

In: 言語処理学会第31回年次大会発表論文集, 2025.

飯塚慎也, 東中竜一郎

適応的対話システムのための終盤の会話を予測する埋め込みモデルの構築 Proceedings Article

In: 言語処理学会第31回年次大会発表論文集, 2025.

津田太郎, 山下紗苗, 井上昂治, 河原達也, 東中竜一郎

Multi-Relational Multi-Party Chat Corpus: 話者間の関係性に着目したマルチパーティ雑談対話コーパス Proceedings Article

In: 言語処理学会第31回年次大会発表論文集, 2025.

山下紗苗, 東中竜一郎

対話要約の種別が対話の引継ぎに及ぼす影響の調査 Proceedings Article

In: 言語処理学会第31回年次大会発表論文集, 2025.

大橋厚元, 飯塚慎也, 姜菁菁, 東中竜一郎

日本語Full-duplex音声対話システムの試作 Proceedings Article

In: 言語処理学会第31回年次大会発表論文集, 2025, (言語処理学会第31回年次大会委員特別賞).

望月翔太, 山下紗苗, 星牟禮健也, 馬場惇, 窪田智徳, 小川浩平, 東中竜一郎

実インタラクション映像から構築したマルチモーダルモデルを用いた人とロボットのインタラクションにおける異常検出 Proceedings Article

In: 言語処理学会第31回年次大会発表論文集, 2025.

周旭琳, 市川拓茉, 東中竜一郎

キャッチコピー共同作成対話コーパスにおける第三者評価と自己評価の関係分析 Proceedings Article

In: 言語処理学会第31回年次大会発表論文集, 2025.

Atsumoto Ohashi, Ryuichiro Higashinaka

Optimizing pipeline task-oriented dialogue systems using post-processing networks Journal Article

In: Computer Speech & Language, vol. 90, pp. 101742, 2025, ISSN: 0885-2308.

Abstract | Links | BibTeX

Atsumoto Ohashi, Ryuichiro Higashinaka

Universal Post-Processing Networks for Joint Optimization of Modules in Task-Oriented Dialogue Systems Proceedings Article

In: Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25), 2025.

2024

角森唯子, 東中竜一郎

パーソナライズ可能な雑談対話システム構築に向けた任意のユーザ情報を踏まえた発話コーパスの構築と分析 Journal Article

In: 自然言語処理, vol. 31, iss. 4, pp. 1635–1664, 2024.

Yuki Sato, Yuya Chiba, Ryuichiro Higashinaka

Investigating the Language Independence of Voice Activity Projection Models through Standardization of Speech Segmentation Labels Proceedings Article

In: Proceedings of Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2024.

Yuki Sato, Yuya Chiba, Ryuichiro Higashinaka

Effects of multiple Japanese datasets for training Voice Activity Projection models Proceedings Article

In: Proceedings of the 27th conference of Oriental COCOSDA (O-COCOSDA), 2024.

Jingjing Jiang, Ao Guo, Ryuichiro Higashinaka

Estimating the Emotional Valence of Interlocutors Using Heterogeneous Sensors in Human-Human Dialogue Proceedings Article

In: Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL) , pp. 718-727, Kyoto, Japan, 2024.

Ao Guo, Shota Mochizuki, Sanae Yamashita, Saya Nikaido, Tomoko Isomura, Ryuichiro Higashinaka

Wizard-of-Oz Dialogue Data Collection for a Mobile Guide Robot Proceedings Article

In: Workshop on Spoken Dialogue Systems for Cybernetic Avatars (SDS4CA), 2024.

Shota Mochizuki, Sanae Yamashita, Tomonori Kubota, Kohei Ogawa, Ryuichiro Higashinaka

Impact of Data Size and Recording Environments on the Performance of Anomaly Detection in Human-Robot Interaction Proceedings Article

In: Workshop on Spoken Dialogue Systems for Cybernetic Avatars (SDS4CA), 2024.

Shota Mochizuki, Sanae Yamashita, Reiko Yuasa, Tomonori Kubota, Kohei Ogawa, Ryuichiro Higashinaka

Learning Anomaly Detection Models for Human-Robot Interaction Proceedings Article

In: Proceedings of the 33rd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) , pp. 1720–1725, 2024.

Haruhisa Iseno, Ryuichiro Higashinaka

Comparative Analysis of Common Ground Representations in Dialogue Systems: a Case Study using the OneCommon Task Proceedings Article

In: Proceedings of the Conversational Grounding in the Era of LLMs Workshop, European Summer School in Logic, Language and Information (ESSLLI) 2024, pp. 24–26, 2024.

姜菁菁，郭傲，東中竜一郎

異種センサを用いたマルチモーダル対話データの収集とセンサ情報と主観評価の関係分析 Proceedings Article

In: 2024年度人工知能学会全国大会（第38回）, pp. 4Xin278-4Xin278, 2024.

Xulin Zhou, Takuma Ichikawa, Ryuichiro Higashinaka

Collecting and Analyzing Dialogues in a Tagline Co-Writing Task Proceedings Article

In: The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), 2024.

Atsumoto Ohashi, Ryu Hirai, Shinya Iizuka, Ryuichiro Higashinaka

JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset Proceedings Article

In: The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), 2024.

Yuiko Tsunomori, Ryuichiro Higashinaka

I Remember You!: SUI Corpus for Remembering and Utilizing Users' Information in Chat-oriented Dialogue Systems Proceedings Article

In: The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), 2024.

Shota Mochizuki, Sanae Yamashita, Rio Suzuki, Ryuichiro Higashinaka

Construction and Evaluation of Sales and Educational Dialogue Systems in Parallel Conversations Proceedings Article

In: Proceedings of the ICRA2024 Workshop: Workshop on 'Society of Avatar-Symbiosis through Social Field Experiments', 2024.

周旭琳, 市川拓茉, 東中竜一郎

キャッチコピー共同作成対話コーパスにおける発話と編集および参照の分析 Proceedings Article

In: 言語処理学会第30回年次大会発表論文集, 2024.

大橋厚元, 東中竜一郎

生成的後処理ネットワークによるタスク指向型対話システムの最適化 Proceedings Article

In: 言語処理学会第30回年次大会発表論文集, 2024.

平井龍, 郭傲, 東中竜一郎

タスク指向型対話システムへの項目反応理論の適用によるユーザのタスク達成能力の推定 Proceedings Article

In: 言語処理学会第30回年次大会発表論文集, 2024.

山下紗苗, 井上昂治, 郭傲, 望月翔太, 河原達也, 東中竜一郎

RealPersonaChat: 話者本人のペルソナと性格特性を含んだ雑談対話コーパス Proceedings Article

In: 言語処理学会第30回年次大会発表論文集, 2024, (若手奨励賞).

大橋厚元, 平井龍, 飯塚慎也, 東中竜一郎

JMultiWOZに対する対話状態アノテーションの付与と対話システムの実装評価 Proceedings Article

In: 言語処理学会第30回年次大会発表論文集, 2024.

望月翔太, 山下紗苗, 湯浅令子, 窪田智徳, 小川浩平, 東中竜一郎

人とロボットのインタラクションにおけるマルチモーダル情報を用いた異常検出 Proceedings Article

In: HAIシンポジウム2024, pp. P-40–P-40, 2024.

Sanae Yamashita, Ryuichiro Higashinaka

Multifaceted Evaluation of Automatically Generated Dialogue Format Summary Proceedings Article

In: The 14th International Workshop on Spoken Dialogue Systems Technology, 2024.

佐藤友紀, 千葉祐弥, 東中竜一郎

複数の日本語データセットによる音声活動予測モデルの学習とその評価 Proceedings Article

In: 人工知能学会研究会資料言語・音声理解と対話処理研究会, pp. 192–197, 2024.

Ao Guo, Ryu Hirai, Atsumoto Ohashi, Yuya Chiba, Yuiko Tsunomori, Ryuichiro Higashinaka

Personality Prediction from Task-oriented and Open-domain Human–machine Dialogues Journal Article

In: Scientific Reports, vol. 14, iss. 3868, 2024.

Abstract | Links | BibTeX

@article{guo_sr2024,

title = {Personality Prediction from Task-oriented and Open-domain Human–machine Dialogues},

author = {Ao Guo and Ryu Hirai and Atsumoto Ohashi and Yuya Chiba and Yuiko Tsunomori and Ryuichiro Higashinaka},

doi = {https://doi.org/10.1038/s41598-024-53989-y},

year  = {2024},

date = {2024-02-16},

urldate = {2024-02-16},

journal = {Scientific Reports},

volume = {14},

issue = {3868},

abstract = {If a dialogue system can predict the personality of a user from dialogue, it will enable the system to adapt to the user's personality, leading to better task success and user satisfaction. In a recent study, personality prediction was performed using the Myers–Briggs Type Indicator (MBTI) personality traits with a task-oriented human-machine dialogue using an end-to-end (neural-based) system. However, it is still not clear whether such prediction is generally possible for other types of systems and user personality traits. To clarify this, we recruited 378 participants, asked them to fill out four personality questionnaires covering 25 personality traits, and had them perform three rounds of human-machine dialogue with a pipeline task-oriented dialogue system or an end-to-end task-oriented dialogue system. We also had another 186 participants do the same with an open-domain dialogue system. We then constructed BERT-based models to predict the personality traits of the participants from the dialogues. The results showed that prediction accuracy was generally better with open-domain dialogue than with task-oriented dialogue, although Extraversion (one of the Big Five personality traits) could be predicted equally well for both open-domain dialogue and pipeline task-oriented dialogue. We also examined the effect of utilizing different types of dialogue on personality prediction by conducting a cross-comparison of the models trained from the task-oriented and open-domain dialogues. As a result, we clarified that the open-domain dialogue cannot be used to predict personality traits from task-oriented dialogue, and vice versa. We further analyzed the effects of system utterances, task performance, and the round of dialogue with regard to the prediction accuracy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

2023

Ryu Hirai, Shinya Iizuka, Haruhisa Iseno, Ao Guo, Jingjing Jiang, Atsumoto Ohashi, Ryuichiro Higashinaka

Team Flow at DRC2023: Building Common Ground and Text-based Turn-taking in a Travel Agent Spoken Dialogue System Proceedings Article

In: 2023.

Atsumoto Ohashi, Ryuichiro Higashinaka

Enhancing Task-oriented Dialogue Systems with Generative Post-processing Networks Proceedings Article

In: The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP2023), pp. 3815–3828, Singapore, 2023.

Shota Mochizuki, Sanae Yamashita, Kazuyoshi Kawasaki, Reiko Yuasa Tomonori Kubota, Kohei Ogawa, Jun Baba, Ryuichiro Higashinaka

Investigating the Intervention in Parallel Conversations Proceedings Article

In: HAI '23: Proceedings of the 11th International Conference on Human-Agent Interaction, 2023, (Best Paper Award Nominee).

Sanae Yamashita, Shota Mochizuki, Kazuyoshi Kawasaki, Tomonori Kubota, Kohei Ogawa, Jun Baba, Ryuichiro Higashinaka

Investigating the Effects of Dialogue Summarization on Intervention in Human-System Collaborative Dialogue Proceedings Article

In: HAI '23: Proceedings of the 11th International Conference on Human-Agent Interaction, 2023.

85 entries « ‹ 1 of 2 › »