Yuya Chiba


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Influence of user personality on dialogue task performance: A case study using a rule-based dialogue system
Ao Guo | Atsumoto Ohashi | Ryu Hirai | Yuya Chiba | Yuiko Tsunomori | Ryuichiro Higashinaka
Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI

Endowing a task-oriented dialogue system with adaptiveness to user personality can greatly help improve the performance of a dialogue task. However, such a dialogue system can be practically challenging to implement, because it is unclear how user personality influences dialogue task performance. To explore the relationship between user personality and dialogue task performance, we enrolled participants via crowdsourcing to first answer specified personality questionnaires and then chat with a dialogue system to accomplish assigned tasks. A rule-based dialogue system on the prevalent Multi-Domain Wizard-of-Oz (MultiWOZ) task was used. A total of 211 participants’ personalities and their 633 dialogues were collected and analyzed. The results revealed that sociable and extroverted people tended to fail the task, whereas neurotic people were more likely to succeed. We extracted features related to user dialogue behaviors and performed further analysis to determine which kind of behavior influences task performance. As a result, we identified that average utterance length and slots per utterance are the key features of dialogue behavior that are highly correlated with both task performance and user personality.

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Variation across Everyday Conversations: Factor Analysis of Conversations using Semantic Categories of Functional Expressions
Yuya Chiba | Ryuichiro Higashinaka
Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation


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Construction and Analysis of a Multimodal Chat-talk Corpus for Dialog Systems Considering Interpersonal Closeness
Yoshihiro Yamazaki | Yuya Chiba | Takashi Nose | Akinori Ito
Proceedings of the 12th Language Resources and Evaluation Conference

There are high expectations for multimodal dialog systems that can make natural small talk with facial expressions, gestures, and gaze actions as next-generation dialog-based systems. Two important roles of the chat-talk system are keeping the user engaged and establishing rapport. Many studies have conducted user evaluations of such systems, some of which reported that considering the relationship with the user is an effective way to improve the subjective evaluation. To facilitate research of such dialog systems, we are currently constructing a large-scale multimodal dialog corpus focusing on the relationship between speakers. In this paper, we describe the data collection and annotation process, and analysis of the corpus collected in the early stage of the project. This corpus contains 19,303 utterances (10 hours) from 19 pairs of participants. A dialog act tag is annotated to each utterance by two annotators. We compare the frequency and the transition probability of the tags between different closeness levels to help construct a dialog system for establishing a relationship with the user.


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Improving User Impression in Spoken Dialog System with Gradual Speech Form Control
Yukiko Kageyama | Yuya Chiba | Takashi Nose | Akinori Ito
Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue

This paper examines a method to improve the user impression of a spoken dialog system by introducing a mechanism that gradually changes form of utterances every time the user uses the system. In some languages, including Japanese, the form of utterances changes corresponding to social relationship between the talker and the listener. Thus, this mechanism can be effective to express the system’s intention to make social distance to the user closer; however, an actual effect of this method is not investigated enough when introduced to the dialog system. In this paper, we conduct dialog experiments and show that controlling the form of system utterances can improve the users’ impression.

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An Analysis of the Effect of Emotional Speech Synthesis on Non-Task-Oriented Dialogue System
Yuya Chiba | Takashi Nose | Taketo Kase | Mai Yamanaka | Akinori Ito
Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue

This paper explores the effect of emotional speech synthesis on a spoken dialogue system when the dialogue is non-task-oriented. Although the use of emotional speech responses have been shown to be effective in a limited domain, e.g., scenario-based and counseling dialogue, the effect is still not clear in the non-task-oriented dialogue such as voice chatting. For this purpose, we constructed a simple dialogue system with example- and rule-based dialogue management. In the system, two types of emotion labeling with emotion estimation are adopted, i.e., system-driven and user-cooperative emotion labeling. We conducted a dialogue experiment where subjects evaluate the subjective quality of the system and the dialogue from the multiple aspects such as richness of the dialogue and impression of the agent. We then analyze and discuss the results and show the advantage of using appropriate emotions for the expressive speech responses in the non-task-oriented system.


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User Modeling by Using Bag-of-Behaviors for Building a Dialog System Sensitive to the Interlocutor’s Internal State
Yuya Chiba | Masashi Ito | Takashi Nose | Akinori Ito
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)