一般社団法人 電子情報通信学会
THE INSTITUTE OF ELECTRONICS,
INFORMATION AND COMMUNICATION ENGINEERS

HCGシンポジウム2017
HUMAN COMMUNICATION GROUP SYMPOSIUM 2017
HCG2017-B-5-2

Conversational Atmosphere Model and Reproduction by Animated Agents
Masahide YUASA
Shonan Institute of Technology, 1-1-25 Tsujido Nishikaigan, Fujisawa, 251-8511
E-mail:yuasa@sc.shonan-it.ac.jp

Abstract Humans not only prefer to speak precisely and to convey information, but also enjoy conversation for its own
sake. This type of conversation plays an important role in establishing bonds of solidarity among participants. In this study, amodel is developed that can portray various types of conversational atmospheres based on the concept of phatic expression,and reproduce conversations and atmospheres using multiple animated agents. A simulation system is also developed toreproduce conversational atmospheres by controlling animated agents’ verbal and nonverbal behaviors. Based on the proposedmodel, a simulation can generate informative or phatic atmosphere.
Keywords Animated agent，character，conversation，atmospherestate of violation of conversational rules; however, it may

1. Introduction
Humans not only prefer to speak precisely and to

make solidarity of friendship. Based on the model, we canconvey information but also enjoy conversation for its

develop conversational robots/agents that can reproduce

ownvarious types of atmospheres, leading to a friendly

sake.

In

conversation

studies[ 1,2],

sucha

conversation is categorized as “phatic expression” [1, 2].

atmosphere for humans.

This type of conversation plays an important role in

To confirm the validity of the model, we develop aestablishing and maintaining bonds of solidarity among

multi-agent simulation system based on the idea ofparticipants [1]. Coates postulated that conversation

autonomous turn-taking agent system in previous studies

among women involves not only the construction of a[5-7].

Thesystem

shared floor, but also comprises an amount of overlap

atmospheres

based

canon

reproduce

theproposed

conversationalmodel.

The(simultaneous talk) [3]. The study also suggested that theatmospheres are created by controlling the animatedoverlap in speech was not a deviant phenomenon, but aagents’ verbal and nonverbal behavi ors. The model may be

way of expressing the solidarity of friendship ; theable to estimate an upcoming mood, or create a specificdeviation is expected in the form of a phatic expression.

mood across multiple situations.

Roger et al. described both cases in which simultaneous

Developing the atmosphere model and investigating thespeech is repaired, and ones in which it is not repaired

mechanism of atmosphere will enable development ofwhen participants conform to the rule that one speakervarious types of application using the atmosphere [8, 9]

starts to speak at a time [4]. When phatic expressions areused, violation of standard conversational rules are2. Overview of Proposed Model

allowed slightly, as the phatic expression takes priority

We hypothesize that phatic communication is a mainover the conversational rules. Thus, the importance offactor in our atmosphere as humans have the desire todeviation as a phatic expression has been described incommunicate with other fundamentally. On the other hand,literature; however, it has not been used for developing

informative (formal) communication is assumed by social

conversational robots/agents. If the relationship between

constraints against phatic communication. For example,

the violation of conversational rules and solidarity ofthere are important conversational rules such as if afriendship is revealed, robots/agents that can make sense

participant starts to speak, the others shou ld not start to doof the unity between robots/agents and humans can beso, and if a participant wants to start to speak, he/shedeveloped.

shouldTherefore, in this study, we develop a nov el model byfocusing

onphaticcommunication

andtheexpress

this[10,11].

Socialrules

makeconversation smooth and avoid silence. These rules aresocialmore rigid in a formal situation (informative atmosphere)

constraint of human communication. The model represents

than in an informal situation (phatic atmosphere). Thus,

two types of atmospheres, (phatic/informative atmosphere

we hypothesize that humans essentially desire phaticandparticipants’communication in an unrestrained ma nner; however, social

conversational behaviors. Phatic atmosphere indicates aconstraints exist that do not allow unconstrained behavior

also

expresses

thevalidityof

in conversation.

3. Representation by Animated Agents

The proposed model is shown in Figure 1. In thisBasedon

theproposedmodel,

wedevelopaexample, there are three participants (P1-P3) and theconversational

figure indicates their behaviors in areas. “Informativeanimated agents. This system is based on the autonomous

atmosphere” is located in the circle, which represents

multi party conversation system [5-7]. From the findingssocial constraints. If there is no circle of social constraints,

of previous studies, we know that turn taking significantly

they are allowed to behave freely in the area, and theinfluences atmosphere [7]. For example, “a lot of turnsituationphatictaking” might produce excited or energetic moods (e.g., ancommunication such as chat or small talk . On the otheramusing conversation), and “little turn taking” might

hand, if the circle of social constraints exists, participants’

imply sorrowful moods (e.g., at funerals).

behaviors are limited by conversational rul es. In this way,

Program Making Language (TVML) in this study [13]. In

the model can express phatic or informative atmosphere bythis system, we can control the timing of turn taking using

using the size of the circle in the center.

the slide bars on the control panel; this generates variousindicatesbehaviors

offriendly

atmospheresimu lation

systemusing

We use TV

atmospheres (Fig 2). For an unbiased evaluation, w e
selected characters who do not show any facial expression,
but can express head directions and mouth movements.
The agents said random words from the word set with nomeaning (e.g., ARABAHIKA or UKUJARAH).
Based on previous studies [5, 1 0], we prepared typicalconversational behaviors in that the next speaker wasselected in the following turn-taking patterns in thesystem.
Figure 1. Phatic / informative atmosphere model andconversationalatmospheresimulation

systemusing

animated agents. P1-P3 represent participants’ behaviors

Pattern 1: When the person finish speaking, he/shelooks at the hearer would be the next speakerin conversation
Pattern 2: The person being looked at by the previous
speaker would be the next speaker
Moreover, in this system, we can choose the size of thesocial constraints; this value and agents’ behaviors aredisplayed in the panel. Thus, we can observe agents’behaviors (turn-taking) and the validity of the behaviors(figure 2).

4. Discussion and Conclusions
Examples of the relationship between t he produced
Figure 2. Controlling the size of social constraints
circle and agents’ behavior

behaviors of agents and the notation of model are shown in
Figure 3. In the current system, we prepared t wo types ofturn-taking;T1: only one of the hearers started to speak (fol lowing
the conversational rule)T2: overlap of utterance occurs (deviation from theconversational rule.)
T2 implies that not only one of the hearers starts to speak,
but also the other hearer starts to speak.notation of the model.
However, it must be known whether the situation has aphatic or informative atmosphere in advance to judge thematching the behavior. It is hard to judge the behavior byobserving only the agents’ behaviors without notation of
the social constraint. Thus, to comprehend the atmosphere ,situation setting (the current situation is phatic orinformative atmosphere) is required in advance. The
approach to prepare the situation settings will be taken up
in future studies.
Moreover, because
expresses

the system only generates andatmospheres,atmosphereswesubjectively,

cansuchasonlyevaluatethebyconducting

aquestionnaire experiment. We should find an appropriate
objective method (i.e., measurement of eye movements orreactiontimes)

andinteractive

methods

againstrobots/agents for future studies.
To summarize, according to the finding from previous
studies that humans’ conversation s have deviation and thepossibility

tomake“solidarity”

offriendship,wedeveloped a conversational model to express the phatic
communication and informative communication. Based on
the model, we developed multiple animated agents tomodel the types of phatic and informative communicat ions.
Figure 3. The model and agents’ behaviors

The reproduction b y the agents were thought to havevalidity. In future, we will conduct an experiment toAs described in the latter, the participant who starts toconfirm the validity of the reproduction.

speak and who was looked at by the previous speaker wasdecided by probability (randomly) in the system; however,

References

the chance level of overlap was chosen depending on the[1] Malinowski, B., “The Problem of Meaning inPrimitive Languages,” in Charles K. Ogden and Ian A.
Richards, The Meaning of Meaning, London: KeganPaul, Trench and Trubner, pp. 296–336, 1923.
[2] Haberland, H., “Communion or communication? A
historical note on one of the 'founding fathers' ofpragmatics,” in Robin Sackmann (ed.), Theoreticallinguistics and grammatical description, Amsterdam:
Benjamins, pp. 163-166, 1996.
[3] Coates, J., “No gap, lots of overlap: Turn -taking
patterns in the talk of women friends. ” In D. Graddol,J. Maybin, & B. Stierer (Eds.), Researching l anguage
and literacy in social context, Philadelphia:
Multilingual Matters, pp. 177–192, 1994.
[4] Roger, D., Bull, P., and Smith, S.,” The Developmentof a Comprehensive System for ClassifyingInterruptions,” Journal of Language and Social
Psychology, Vol 7, Issue 1, pp. 27-34, 1988.
[5] Yuasa, M., Tokunaga, H., and Mukawa, N.,“Autonomous Turn-Taking Agent System based onBehavior Model,” HCI International 2009, pp.
368-373, 2009.
[6] Yuasa, M., and Mukawa, N., “Building ofTurn-Taking Avatars that Express Utterance Attitudes- A Social Scientific Approach to Behavioral Designof Conversational Agents-,” HCI 2011. pp.101-107,

size of social constraint.
Figure 3(a)showsthatnosocialconstraints

andturn-taking patterns were chosen freely. Both single
turn-taking (only one speaker starts to speak) and overlap
were present. A slight bustling and friendly atmosphere
could be created by overlap, and phatic atmosphere could
be produced by the system. The (b) in Figure 3 expresses
that there was social constraint and the turn -taking
behaviors were limited. Only single turn -taking wasproduced and it was felt monotonous.
Furthermore, we used the special parameter that agent
could deviate the constraint within social const raint.
Figure 3(c) shows that only P3’s behavior deviates
although there was social constraint. Th e situation meantthat P1 and P2 behaved as in an informative atmosphere(formal communication), however P3 behaved like theatmosphere was phatic. The behavior may not match theatmosphere. The agents’ behavior was valid as the2011.
[7] Yuasa, M., “Can Animated Agents Help us Create
Better Conversational Moods? - An Experiment on
the Nature of Optimal Conversations -,” HCII2014,
8th International Conference, UAHCI 2014, Held as
Part of HCI International 2014, Heraklion, Crete,Greece, June 22-27, 2014, Proceedings, Part IV, pp.
634-640, in "Universal Access in Human -Computer
Interaction. Design for All and Accessibility
Practice", 2014.
[8] Yuasa, M., and Morimoto, D., “Do You Follow Angel
Agent's Advice? A Pilot Study for Decision Making
Support by Multiple Animated Agents, ” SCIS & ISIS
2016, 2016.
[9] Yuasa, M., and Nanba, K., “Restaurant-Guide Site
Using Atmosphere Expressed by Abstract Characters,“ IEICE-AI2017, vol. 117, no. 72, AI2017 -6, pp.
25-26, 2017.
[10] Yuasa, M., Mukawa, N., Kimura, K., Tokunaga, H.,and Terai, H., “An Utterance Attitude Model in
Human-Agent
Communication:
FromGood
Turn-taking to Better Human-Agent Understanding,”
CHI Extended Abstracts 2010, pp. 3919-3924, 2010.
[11] Duncan, S., “Some signals and rules for taking
speaking turns in conversations ,” Journal ofPersonality and Social Ps ychology 23, pp. 283-292,
1972.
[12] Matsusaka, Y., Fujie, S., and Kobayashi, T.:“Modeling of Conversational Strategy for the Robot
Participating in the Group Conversation ,” In: Proc.
Eurospeech 2001, pp. 2173–2176, 2001.
[13] TV
Program
MakingLanguage(TVML),
http://www.nhk.or.jp/strl/tvml/.