Asahi Hentona


2025

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User Willingness-aware Sales Talk Dataset
Asahi Hentona | Jun Baba | Shiki Sato | Reina Akama
Proceedings of the 31st International Conference on Computational Linguistics

User willingness is a crucial element in the sales talk process that affects the achievement of the salesperson’s or sales system’s objectives. Despite the importance of user willingness, to the best of our knowledge, no previous study has addressed the development of automated sales talk dialogue systems that explicitly consider user willingness. A major barrier is the lack of sales talk datasets with reliable user willingness data. Thus, in this study, we developed a user willingness–aware sales talk collection by leveraging the ecological validity concept, which is discussed in the field of human–computer interaction. Our approach focused on three types of user willingness essential in real sales interactions. We created a dialogue environment that closely resembles real-world scenarios to elicit natural user willingness, with participants evaluating their willingness at the utterance level from multiple perspectives. We analyzed the collected data to gain insights into practical user willingness–aware sales talk strategies. In addition, as a practical application of the constructed dataset, we developed and evaluated a sales dialogue system aimed at enhancing the user’s intent to purchase.

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Analyzing Dialogue System Behavior in a Specific Situation Requiring Interpersonal Consideration
Tetsuro Takahashi | Hirofumi Kikuchi | Jie Yang | Hiroyuki Nishikawa | Masato Komuro | Ryosaku Makino | Shiki Sato | Yuta Sasaki | Shinji Iwata | Asahi Hentona | Takato Yamazaki | Shoji Moriya | Masaya Ohagi | Zhiyang Qi | Takashi Kodama | Akinobu Lee | Takashi Minato | Kurima Sakai | Tomo Funayama | Kotaro Funakoshi | Mayumi Usami | Michimasa Inaba | Ryuichiro Higashinaka
Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue

In human-human conversation, interpersonal consideration for the interlocutor is essential, and similar expectations are increasingly placed on dialogue systems. This study examines the behavior of dialogue systems in a specific interpersonal scenario where a user vents frustrations and seeks emotional support from a long-time friend represented by a dialogue system. We conducted a human evaluation and qualitative analysis of 15 dialogue systems under this setting. These systems implemented diverse strategies, such as structuring dialogue into distinct phases, modeling interpersonal relationships, and incorporating cognitive behavioral therapy techniques. Our analysis reveals that these approaches contributed to improved perceived empathy, coherence, and appropriateness, highlighting the importance of design choices in socially sensitive dialogue.

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Identification and Analysis of Identity-Centric Elements of Character-Likeness in Game Scenario
Shinji Iwata | Koya Ihara | Shiki Sato | Jun Baba | Asahi Hentona | Masahiro Yamazaki | Yuki Shiotsuka | Takahiro Ishizue | Akifumi Yoshimoto
Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue

Generating and evaluating character-like utterances automatically is essential for applications ranging from character simulation to creative-writing support. Existing approaches primarily focus on basic aspects of character‐likeness, such as script-fidelity knowledge and conversational ability. However, achieving a higher level of character‐likeness in utterance generation and evaluation requires consideration of the character’s identity, which deeply reflects the character’s inner self. To bridge this gap, we identified a set of identity-centric character-likeness elements. First, we listed 27 elements covering various aspects of identity, drawing on psychology and identity theory. Then, to clarify the features of each element, we collected utterances annotated with these elements from a commercial smartphone game and analyzed them based on user evaluations regarding character-likeness and charm. Our analysis reveals part of element-wise effects on character‐likeness and charm. These findings enable developers to design practical and interpretable element-feature-aware generation methods and evaluation metrics for character-like utterances.

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Key Challenges in Multimodal Task-Oriented Dialogue Systems: Insights from a Large Competition-Based Dataset
Shiki Sato | Shinji Iwata | Asahi Hentona | Yuta Sasaki | Takato Yamazaki | Shoji Moriya | Masaya Ohagi | Hirofumi Kikuchi | Jie Yang | Zhiyang Qi | Takashi Kodama | Akinobu Lee | Masato Komuro | Hiroyuki Nishikawa | Ryosaku Makino | Takashi Minato | Kurima Sakai | Tomo Funayama | Kotaro Funakoshi | Mayumi Usami | Michimasa Inaba | Tetsuro Takahashi | Ryuichiro Higashinaka
Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue

Challenges in multimodal task-oriented dialogue between humans and systems, particularly those involving audio and visual interactions, have not been sufficiently explored or shared, forcing researchers to define improvement directions individually without a clearly shared roadmap. To address these challenges, we organized a competition for multimodal task-oriented dialogue systems and constructed a large competition-based dataset of 1,865 minutes of Japanese task-oriented dialogues. This dataset includes audio and visual interactions between diverse systems and human participants. After analyzing system behaviors identified as problematic by the human participants in questionnaire surveys and notable methods employed by the participating teams, we identified key challenges in multimodal task-oriented dialogue systems and discussed potential directions for overcoming these challenges.

2022

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Japanese Named Entity Recognition from Automatic Speech Recognition Using Pre-trained Models
Seiichiro Kondo | Naoya Ueda | Teruaki Oka | Masakazu Sugiyama | Asahi Hentona | Mamoru Komachi
Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation