How do we interact with mechanical systems such as PC, smartphone and so on? Users command something to the system, and the system always accepts and reacts it. That kind of relationship can be named "leader-follower" relationship. On the other hand, thinking about a scene that you have a walk in a park with your partner, there are neither a definite leader nor a follower. You and your partner co-adjust the walking direction and pace by considering each other's intention and feeling from implicit cues. Such relationship has "intersubjectivity" that people share their feeling and intention with others. This study is motivated to build "intersubjective relationship" between human and robot. In this paper, we propose the concept of a side-by-side walking robot "Mako-no-te".

We propose a portable robot, named "Pocketable-Bones", that fits into a user's breast pocket and communicates with the user "side-by-side", which involves coordinating the direction in which the user is looking and the object of interest. In this paper, we discuss the development of a platform for the robot and the hardware configuration needed to establish the human-robot "side-by-side" communication. In our presentation, we will demonstrate the side-by-side communication with the robot and the participants can experience it.

This paper presents an overview of Talking-Bones where the robot aims to communicate with humans in a conversation recalling together. Talking-Bones exhibits encouraging behaviors by forgetting some words in a story and asking humans to help to recall the words together in order to continue telling the story. In our field work, we observed that people found the forgotten words together and enjoyed teaching the robot often laughing and smiling. From this exercise in Joint-Remembering, we suggest that Talking-Bones has the ability to bring out helping behaviours and facilitate communication. In this paper we describe the concept of Talking-Bones and details of the robot design. Also, we describe part of the observed interaction.

Recently, the applications of conversational robots have been gaining popularity due to their potential in providing information while engaging the user in a conversation. However, when a user's attention is already focused on a task, engaging them in conversation may be difficult or even risky. The Human-Robot Interaction (HRI) field should consider interaction methods where a conversational robot can keep the user informed but without the obligation of engagement in the conversation. In this study, we discuss such an approach within a driving scenario by utilizing a multi-party social robot platform that comprises three minimalistic conversational robots, which possesses the feature of being able to decrease the number of directed utterances toward a driver through a turn-taking process among the robots. The results of this study revealed that overhearing information from the multi-party conversation of driving agents is perceived as possessing more life-like characteristics compared to a conventional, one-to-one communication-based approach that directly addresses the driver. Moreover, the proposed approach reduced the distraction level and increased the enjoyment of the drivers.

The general principle about human-robot conversation is that the conversation of a robot should emphasize on providing complete information in a single utterance, without the necessity of a human asking further questions. On the other hand, information deficiency is found commonly in human-human conversation. In particular, between a child and a caregiver; even though the child has a limited speaking ability, they can build a deep bond by means of the positive and interactive support of their caregiver. Unlike many kinds of research whose aim is to make a robot possess a superior ability to have a natural conversation with a human, in this research, we focus on the incompleteness in a robots' conversation by utilizing some strategies such as information deficiency and ellipsis. Herein, it is important to understand the behaviors and responses of the human partner in such a human-robot conversation. This study aims to analyze human responses when a robot speaks to a human with insufficient words. Accordingly, we constructed a syntactic method to create a deficiency in the elements of uttered sentences to analyze the behaviors and replies of a human in a human-robot conversation. The results showed that when the robot used "Semantically Incomplete Utterance"; which means the robot has unclear references in its utterance, the human partner increased the number of questions to the robot, talked further about the new information related to the topics and decreased the number of slight responses. Consequently, the incompleteness in the utterance of a robot attracted cooperative human responses, and the participants increased participation in the domain of conversation.

In this study, we investigated the nature of the triadic interaction between persons within a cooperative play by utilizing a panel-type robot platform, INAMO. INAMO generates its movement by a joystick that triggers acceleration of the flywheels where their rotation enables the robot to move around the electromagnets which provide connection of two INAMOs. We set up an experiment based on a cooperative play mediated by INAMOs to examine the effects of a common task and a social reference on subjects' controlling skills, communication each other and interestingness of the game. We also analyzed the performance of the subjects and their impressions on the cooperative play. The results demonstrated that the existence of a common task and the social reference have significant effects on such triadic interactions.

Robots are expected to become present in society in increasing numbers, yet few studies in human-robot interaction (HRI) go beyond one-to-one interaction to examine how characteristics of robot groups will affect HRI. In particular, people may show more negative or aggressive behavior toward entitative (i.e., cohesive) robot groups, like they do toward entitative human groups, compared to diverse groups. Furthermore, because people in collectivist (e.g., Japan) and individualistic (e.g., US) cultures respond to groups and to cues of entitativity differently, entitative robot groups may affect people differently across such cultures. This study examines how robot Entitativity Condition (Single Robots, Diverse Group, Entitative Group) and Country (USA, Japan) affect emotions toward, mind attributions to, and willingness to interact with robots. Results indicate that Entitative robot groups, compared to Single robots, were viewed more negatively. Entitative robots were also more threatening than Diverse robots. Diverse robot groups, compared to Single robots, were viewed as having more mind, and participants were more willing to interact with them. These findings were similar in the USA and Japan. This indicates that robot group entitativity and diversity is critical to keep in mind when designing robots.

Recently, many studies have been conducted on increasing the automation level in cars to achieve safer and more efficient transportation. The increased automation level creates room for the drivers to shift their attention to non-driving related activities. However, there are cases that cannot be handled by automation where a driver should take over the control. This pilot study investigates a paradigm for keeping the drivers' situation-awareness active during autonomous driving by utilizing a social robot system, NAMIDA. NAMIDA is an interface consisting of three sociable driving agents that can interact with the driver through eye-gaze behaviors. We analyzed the effectiveness of NAMIDA on maintaining the drivers' attention to the road, by evaluating the response time of the drivers to a critical situation on the road. An experiment consisting of a take over scenario was conducted in a dynamic driving simulator. The results showed that existence of NAMIDA significantly reduced the response time of the drivers. However, surprisingly, NAMIDA without eye-gaze behaviors was more effective in reducing the response time than NAMIDA with eye-gaze behaviors. Additionally, the results revealed better subjective impressions for NAMIDA with eye-gaze behaviors behaviors.

We present a novel assistive method for leading casual joggers by showing a virtual runner on see-through head-mounted display they worn. It moves at a constant pace specified in advance by them, and its motion synchronizes the user's one. People can always visually check the pace by looking at it as a personal pacemaker. They are also motivated to keep running by regarding it as a jogging companion. Moreover, proposed method overcomes safety problem of AR apps. Its most body parts are transparent so that it doesn't obstruct their view. This study, thus, may contribute to augment daily jogging experience.

We propose a multi party conversational social interface NAMIDA through a pilot study. The system consists of three robots that can converse with each other about environment throughout the road. Through this model, the directed utterances towards the driver diminishes by utilizing turn-taking process between the agents, and the mental workload of the driver can be reduced compared to the conventional one-to-one communication based approach that directly addresses the driver. We set up an experiment to compare the both approaches to explore their effects on the workload and attention behaviors of drivers. The results indicated that the multi-party conversational approach has a better effect on reducing certain workload factors. Also, the analysis of attention behaviors of drivers revealed that our method can better promote the drivers to focus on the road.

This paper presents NAMIDA, social interface consisting of three robots that help the driver to navigate by considering him as a bystander in a multi-party conversation between the agents. Through this model the cognitive workload of the driver can be reduced compared to the conventional one-to-one communication based approach that directly addresses the driver. We set up an experiment to compare the multiparty conversation based NAMIDA (MPCN) and the one-to-one conversation based NAMIDA (OOCN) to explore the effects of both methods on the cognitive workload factors and attention behaviours of the participants. The results showed that the MPCN system yields reduction in certain workload factors which can help the driver in increasing his attention on the road.

It is still an enormous challenge within the HRI community to make a significant contribution to the development of a robot's utterance generation mechanism. How does one actually go about contributing and predicting the future of robot utterance generation? Since, our motivation to propose a robot's utterance generation approach by utilizing both addressivity and hearership. Novel platform of Talking-Ally is capable of producing an utterance (toward addressivity) by utilizing the state of the hearer's behaviors (eye-gaze information) to persuade the user (states of hearership) through dynamic interaction. Moreover, the robot has the potential to manipulate modality, turn-initial, and entrust behaviors to increase the liveliness of conversations, which are facilitated by shifting the direction of the conversation and maintaining the hearer's engagement in the conversation. Our experiment focuses on evaluating how interactive users engage with an utterance generation approach (performance) and the persuasive power of robot's communication within dynamic interactions.

We developed soccer ball-shaped interactive artifacts (COLUMN) consisting of eight modules that are connected to twelve servomotors. In the interaction, COLUMN becomes a social mediator to prompt the connectivity of the users. We claim that the above process generates a variety of user's interpersonal coordinates and these can be mapped to the shape of COLUMN's. Therefore, the motivation of our study is to extract the patterns of user's interpersonal coordination. It is also interesting to explore how these patterns lead to imagine behavior for an artifact which has different degree of freedom of its body than the existing.

The advantage of the proposed approach is that users can invent their own communication protocol (based on the knock patterns) to communicate with the creature. This approach is a novel concept to establish future human-robot communication protocols within many contexts or human centric applications. However, through symbolic communication (knock-based communication) a human is able to convey to the robot to adapt and communicate with their personalized communication protocol.

We investigate the potentiality of sociable spotlights (sociable artifacts) to change the participants' roles by providing turn-yielding signals at the Transition Relevance Place (TRP) by changing the artifacts' behaviors (the effect of colors combined with the artifact behaviors as a bunch) that moot the state of the conversation.

In this study we develop Core Less Unformed Machine (COLUMN) as novel & transformable robotic platform to explore how visually mediated information is useful to coordinate (interpersonal coordination) to establish connectedness of three participants to obtain COLUMN's behaviors (transformable rolling motions).

In this paper, we propose a MAWARI-based social interface as an interactive social medium to broadcast the information to users. The interface consists of three creatures (MAWARIs) and is designed with minimalism designing concepts. MAWARI is a small scale robot that has only body gestures to express (or interact) its attractive social cues. The participant's role is reduced to that of a bystander when the interface is of a passive social state. In this context, the user does not need to participate in the conversation but still gains information without exerting effort (i.e., less conversational workload).

We developed a creatures-based social dining table that can communicate through a knocking sound, which in Japanese is pronounced as "KonKon." Our main focus was to create a minimal number of cues for a proto-communication by establishing social interactions between a creature and a human. In particular, humans used the "KonKon" interface to communicate with a creature to demonstrate the social behaviors necessary to adapt to a person's intentions. The creature used a mutual adaptation model for achieving a more ideal adaptation during the interactions. In the experimental results, we discuss the concept of the creature and indicate the effectiveness of the communication-protocol on the "KonKon" interface for mutual adaptation.

We developed a Sociable Trash Box (STB) as a children-assisted robot able to collect the trash in order to convey its intentional stance to children. The STB is capable of engaging manifold affiliation behaviors to build a social rapport with children by collecting the trash around their environment. In particular, the STB is a child-dependent robot that walks alone in a public space for tracing humans and trash for the purpose of collecting the trash. The robot is incapable of collecting the trash by itself, and it engages by using interactive behaviors and vocalizations to make a social coupling with children based on the robot's anticipation to accomplish its goal. The present experiment investigates how STB behaviors are effective in conveying intentions to evoke children's social interactions and to assist in collecting the trash in their environment.

A sociable PC (SPC) is capable of engaging and interacting with social cues while users use it. SPC is a kind of artifact which is capable of coordinating and synchronizing its behaviors based on user attention and information on a display. In particular, SPC can exhibit behaviors to induce a trust through social rapport with the user while responding to the user's behaviors and activities on a PC. We used the concept of a minimalism designing mechanism to invent the SPC. The SPC appearance is much like soft "Tofu," so the user can touch and sense it. The SPS can also provide feedback to the user using attractive social cues such as shaking its body, displaying an attractive motion and joint attention with the user, etc.

The STB is capable of engaging manifold affiliation behaviors to build a social rapport toward the goal of collecting trash around an environment. In particular, STB is a child-dependent robot that walks alone in a public space for the purpose of tracing humans and trash and to collect the trash. In a crowded space, STBs move toward the trash by engaging with an attractive twisting motion (behaviors) and vocal interaction to convey STB's intention to children. Our STB robot is incapable of collecting the trash by itself. In this sense, children have to infer a robot's intentional stance or expectation for interaction with the STB. To collect trash while creating social rapport with children is a novel concept. The STB engages with twisting and bowing motions when children put trash into an STB container.

In this paper, a creature-based futuristic sociable dining table is proposed that communicates through a knock on a table. The main objective was to create a minimal number of cues for protocol communication for the purpose of establishing social interactions between a creature and a human. The creature uses a knock (within a specific period) with a Temporal Difference (TD) learning model to learn and to adapt to a user's intentions, and the creature moves a different direction (right, left, straight, and back) on a table based on the user's knock. By ascertaining the creatures' behaviors, the user can convey his/her intentions by a number of knocking sounds while looking at the creature adaption. The creature is capable of doing mutually adaptive learning through a TD model in real time to satisfy the user's goal or intentions. In the context of the experimental results, we discuss the concept of creatures and indicate the effectiveness of the communication-protocol with the “knocking” interface for reciprocal adaptations.

A computer installation that enables a person to rediscover his/her own identity is proposed. Aiming to stimulate an individual’s creativity and expand a new possibility of communication, we expanded how an individual can play in a sandbox electronically by enabling the individual to interact with it. The audio-visually aided sandbox acquires a model of the person playing in the sandbox. This model is used to display an image of the person’s ego. We call the image the person’s “alter ego” because it interactively retains the characteristics of the person, apart from his/her own physical existence. The interaction between the subject and the alter ego helps the subject realize and thereby more deeply recreate his/her own identity.

This paper describes the development of a portable speech interpreter by which the user can look for words and relating sentences easily using his/her voice. The prototype uses a RISC microprocessor for the embedded use, resulting in a compact body of 15cm(W) and 6cm(H). The voice user interface is helpful, especially in small devices, but it has a serious problem related to the recognition errors. The total user interface must be designed carefully to minimize the inconvenience caused by the recognition errors. We have developed an interface in which the confinement of the dictionary realizes the quick and accurate recognition, and the syllable correction procedure provides an easy way to correct recognition errors. These features make it possible to input any words, which are found in a standard Japanese dictionary. Experimental evaluations show that the N-best recognition rate for words and syllables are acceptable.

The paper presents an evaluation method to assess impressions toward a computer-generated creature through human-computer interaction. The aim of our study is to construct a mechanism on a computer to realize empathic interaction between humans and creatures. In this paper, we examine the e ect on personality cognition of a virtual creature when the creature replies with di erent timing to a human utterances. The creature has an abstract appearance and a non-linguistic voice. We control the following three conditions for timing of the creature's response: a) alternation, b) overlap, and c) neutral condition. As a result, we found that the evaluation value of the alternation condition shows more positive behavior than that of the overlap and neutral conditions when the creature has the above features.

In this paper, we present a general framework and architecture for maintaining dialogue coordination in spoken dialogue systems, in which intended behaviors and goals are incrementally performed during the course of maintaining dialogue coordination. The dialogue structure emerges as a result from interaction between user and the dialogue system. The key feature of this design for the systems is to use multiple situated-agents for coordinating communicative acts that are realized as a hierarchy of autonomous behaviors by using a subsumption architecture. In this architecture it should be noted that the lower-level behaviors act autonomously for maintaining the dialogue coordination and are linked to the specifications from higher-level behaviors for dialogue management. In order to make the behavior of the system social, in general, the maintaining of dialogue coordination takes priority over the realization of intended goals of the system as a dialogue participant. We introduce an under-specification strategy for controlling the preference of the concurrent behaviors. This is in contrast to the classical, top-down approach to dialogue coordination.

This paper discusses the effectiveness of human-computer interaction in our prototype system “Talking Eye”, which is based on social behaviors in self-motivated dialogue. Talking Eye system consists of autonomous creatures having the emergent computation architecture with the advantage of selfmotivated dialogue. We performed an experiment using subject’s impression to illustrate the effectiveness of selfmotivated dialogue with the Talking Eye system. The result was obtained that they could find personal nature during interaction even if they could not accomplish their conversational purpose. The main goal of this work is to build a mechanism for autonomous creatures that promotes a more consensual feeling through its interaction with humans.

In traditional studies of multiagents, the entire group of multiagents has been regarded as a single learning system. It is, however, difficult for us to realize such a learning mechanism in the real world because each agent is exposed only to local interactions with others. Therefore, each agent must acquire a capability, "sociality", which finds its own role or niche in the social environment, even if the individual's learning system is self-closed. In this paper, we emphasize that the emergence of "sociality" seems to depend on the dual capabilities of an agent's referencing; self-referential and social-referential abilities. In addition, we present a learning model of an agent having such dual referencing capabilities as a bi-referential model, in which each referencing capability is implemented by an evolutional computation method of classifier system. We present simulated results obtained by the proposed bi-referential model and also show the results obtained when the available resources are changed. Finally, we discuss the dynamic characteristics of the behaviors emerging within the society of agents.

The author presents an efficient parsing algorithm for integrating the search problems both in speech and language processing in general use for spoken language systems (SLSs). The parsing algorithm is an extension of the finite-state-network (FSN)-directed, one-pass search algorithm to one directed by a context-free grammar or a unification-based grammar with retention of the frame-synchronous procedure. This integrating algorithm can approximately find a global optimal sentence hypothesis, and it avoids the overhead of hierarchical systems based on the lattice parsing approach. The computational complexity of this algorithm is proportional to the length of the input utterance. As the search process in speech recognition can directly account for the predictive information, this framework can be extended to the SLS to deal with dynamically varying constraints in a dialogue situation.>