Effects of a Listener Robot with Children in Storytelling
Yumiko Tamura
ATR-IRC, Doshisha Univ.
Kyoto, 619-0288, Japantamura2016@sil.doshisha.ac.jp
Takamasa Iio
ATR-IRC, Osaka Univ.
Kyoto, 619-0288, Japan
iio@atr.jp

Mitsuhiko Kimoto
ATR-IRC, Doshisha Univ.
Kyoto, 619-0288, Japankimoto2013@sil.doshisha.ac.jp
Katsunori Shimohara
Doshisha Univ.
Kyoto, 602-8580, Japankshimoha@mail.doshisha.ac.jp

ABSTRACTThis paper investigates the effects of a listener robot thatjoins a storytelling situation for children as a sideparticipant. For this purpose, we develop a storytellingrobot system that consists of both reader and listener robots.
Our semi-autonomous system involves a human operator
who makes correct responses and provides easily
understandable answers to the children’s questions during
storytelling. We develop a gaze model for the natural andautonomous gaze behaviors of a reader robot by
considering multiple listeners and a storytelling object (adisplay that shows images). We conducted an experimentwith 16 children to investigate whether they preferredstorytelling with/without the listener robot and the changesof speech activities during the storytelling. Children
preferred storytelling with the listener robot to storytellingwithout it. Their speech activities decreased when thelistener robot was involved in the storytelling.
Author keywords

Storytelling; human-robot interaction; two robots;
ACM Classification Keywords

H.5.2. User Interfaces: Interaction styles;
INTRODUCTION

Storytelling is a common human activity in childcare
situations, it plays important roles in the language
development of children and improves their language
complexity [1, 2]. Based on its obvious importance, humanagent and human-robot interaction researchers have focusedon the development of storytelling systems for children [39]. For instance, researchers explored the potential ofstorytelling systems for supporting children’s language
development [7, 8]. Using two robots enables different

Masahiro Shiomi
ATR-IRC
Kyoto, 619-0288, Japanm-shiomi@atr.jp
Norihiro Hagita
ATR-IRC
Kyoto, 619-0288, Japan
hagita@atr.jp

storytelling roles to be assigned, and this strategy might
engage children more deeply and intently during
storytelling [10].
We are also interested in the possibilities of using two
robots for storytelling. Past research used two robots forstorytelling, e.g., two readers by role-playing during
storytelling [10] or two listeners for children’s storytelling[11]. However, our perspective is different; we areinvestigating the effects of a listener robot that behaves likea side-participant, which is a ratified participant during
conversations [12, 13]. Several research works reported thatusing two robots to show their conversations (speaker andlistener robots) to people benefits information providing
tasks [14] [15]. Similar effects might occur in storytellingwith children.
In this study, we investigate the effects of a listener robot ina storytelling context by developing a semi-autonomousstorytelling-robot system (Fig. 1). We deploy a semiautonomous approach to accurately respond to such random
behaviors of children as asking questions during
storytelling to avoid speech recognition difficulties withchildren [16], by involving a human operator. Also, wedeveloped a gaze controller model for the reader robot
during storytelling to naturally and autonomously control
its gaze behaviors. During storytelling, the listener robot
actively behaves as a side-participant: asking the reader
robot questions instead of the children, nodding during
storytelling, etc.

Fig. 1 Storytelling with two robots

In this study, we address the following research question:-Will children prefer a storytelling situation with bothreader and listener robots?
-Will a storytelling situation with both reader and listenerrobots encourage or suppress children’s speech activities?
RELATED WORK

Based on the progress of information technologies, using
multi-media tools in storytelling has become increasingly
popular. In fact, virtual agents and physical robots are often
used as readers. With them, several researchers havedeveloped autonomous storytelling systems for children.
For example, Fourati et al. developed a virtual agent that
displays facial expressions of appraisals related to story
events and experimentally investigated its capabilities withchildren [9]. Bernardini et al. developed intelligent virtual
agents for fostering social communication in autistic
children through storytelling [17]. These works showed
how virtual agents can be used as storytellers for children
and their effectiveness.
Robots are also used as storytelling agents in education
contexts [18]. For instance, Fridin developed a robot thattells two prerecorded stories to small groups of children andshowed that it improved their cognitive and motor
performances [6]. Kory et al. developed a storytellingsystem using a robot with preschool children to support
their language development [7]. Storytelling-robot systems
are used not only for storytelling but also for understanding
children’s behaviors. For example, Leite et al. compared
how children’s behaviors changed during storytelling withindividual and group interactions through role-play-based
storytelling with multiple robots [10]. Another interesting
storytelling trial with robots investigated the effects of an
attentive listening robot on storytelling with children [11].
These research works also scrutinized the possibilities ofusing robots in storytelling contexts.
Similar to these research works, we developed a storytellingsystem using tow robots for children; however, our main
aim is different from this past research work. In this study,
we focused on the effects of a listener robot during
storytelling toward children. Past research works showed
the effectiveness of using two robots to show conversations
to people [14, 19], even if their tasks were different fromstorytelling for children. Even though we believe that using
two robots to create third-party conversations in storytelling
contexts will more deeply attract children and modify theiractivities, no such effects have been unveiled yet.
SYSTEM OVERVIEW

Figure 2 shows an overview of our developed system thatconsists of the following components: human-tracking
system, gaze model, reader robot, listener robot, and ahuman operator who controls the speech recognition andbehavior selector. The reader robot uses a display to showeach page of the picture book during the storytelling. The
details of each component are described as follows.
Human-tracking System

We used one depth sensor (Kinect V2) in the environment
to estimate the positions of the children. The range forrecognizing a person is from 0.5 to 4.5 m, the field’shorizontal angle is 70°, and the field’s perpendicular angle
is 60°. This system sends the estimated head positions of
the children using Kinect V2 libraries to other components
by a network connection.
Gaze ModelIn this study the reader robot must control its gaze by
considering the children, the listener robot, and the display
for natural gaze behaviors because we used a display thatshows images during storytelling. Since several gazemodels have already been proposed in multi-party
conversations [20] [21] [22], we extended the existing a
conversational gaze models for humanlike robots [20]during storytelling with three-party conversations to deal
with similar contexts. Moreover, we addressed the presenceof an additional gaze target (a display) to apply this model
to our system.
In our model, we changed the gazing target ratios at the
beginning of each sentence because a previous gaze modelchanged the gazing target ratios during storytelling [20].
When there is a listener robot in the model, the gazing
targets are the display, the children, the listener robot, andthe environment. Following past research work, we set ourreader robot to look at the display with 0.70 probability atthe beginning of each sentence and at the listeners with 0.73
probability at the non-beginning of each sentence. Based on
the previously defined gaze ratio probability [20], we set
the values at the beginning of the targets to 70.0%, 3.9%,
3.3%, and 22.8% and the values at the not-beginning of thetargets to 10.3%, 39.5%, 33.5%, and 16.7%. Thus, at the
beginning of each sentence, the reader robot mainly looks at
the display; at the not-beginning of each sentence, thereader robot mainly looks at the children or the listenerrobot. When the gaze target is the environment, the gazeangle was randomly decided from the front of the robot tothe display. Without a listener robot, the gaze target ratio isadded to the children’s ratios. We decided that the gazetarget changes every three seconds.

Depth
sensors

Human
tracking

Behaviors

SpeechsynthesisMic

Speechrecognition

Behavior
selector

GesturecontrolGaze model

Page
control

Operator involved
Autonomous

Fig. 2 System overview

Reader/listener
robots

Displayrules. Our system enables the operator to select the speech
recognition results based on pre-determined candidates, andthen the robots autonomously decide their actions using the
speech recognition results.
If no appropriate answers exist towards children’s questions,the operator uses Sota’s text-to-speech function to answer
them quickly. Also, the operator decides the timing of theutterances during storytelling, because we can’t predict
when children will ask the robots questions.
Details of Implemented Behaviors

An overview of the dialogue flow is summarized in Fig. 4.
After the storytelling begins, the reader robot looks at thechild and the listener robot and starts to read. Both robots
semi-autonomously interact with the children, except forthe speech recognition and behavior selections.

Fig 3 Sota

Introduction

Display the first page
Storytelling(reading one sentence)
Does child say
something?

Yes

No
Yes

Did childspeak within aminute?

Is there aquestion?

No

Yes

No

Questions bylistener robot

Answers byreader robot

Answers byreader robot

Go to next
page?

No
Were all of thesentence read?

No

Yes

Go to next page

To implement our storytelling behaviors, we used two
picture books: Etwas von den Wurzelkindern by Sibylle vonOlfers (Nekko umare no kobito tachi in Japanese) and
Zucchini of Zuzu by Leo Rivas (Zuzu no Zukki-ni inJapanese). Average reading times by our system are 5.5 and3.5 minutes, respectively. We chose these books to avoid
already known situations in our experiment, because bothare written for young children, and neither are very
common in our country yet.
Introduction
The reader and listener robots greet each child by name andintroduce themselves through conversations. The children’s
names were registered before the experiment. For thechildren’s acclimatization, both robots made small talkabout the weather, for example. After introducing
themselves, the robots start to tell the story.
Storytelling

Yes

FarewellFig. 4 Dialog flow

The reader robot slowly reads a sentence of the picturebook aloud, and then the listener robot nods once after eachsentence. The reader robot controls the image on the display
based on the storytelling’s progress. During the storytelling
the robot reader gaze behavior is controlled by the proposedgaze model.

Robot

Asking/answering questions between the robots

Figure 3 shows Sota, an interactive humanoid robot
characterized by its humanlike physical expressions. We
used two Sota robots: a reader and a listener. Sota has eight
DOFs: three in its head, one for the shoulders, elbows, andbase. It is 28 cm tall and is equipped with a voice synthesis.
The LED on its mouth blinks depending on the sound level
to indicate speaking. The robot gazes are autonomously
controlled by the proposed gaze model described above.
The robots’ shoulders slowly move as an idling behavior.

If the child fails to ask the reader robot a question within aminute, the listener robot asks a question itself, which thereader robot simply answers. Both the question andanswering behaviors are pre-defined, and their timings arecontrolled by the operator. We prepared 38 asking
behaviors and 29 answering behaviors based on thecontents of the two books. For example, the listener robot
might ask “what is a forget-me-not?” and the reader robot
answers: “a plant with a blue flower.” In some cases, since
one answer behavior was used for different asking
behaviors, the numbers of asking and answering behaviors
are different.

Operator

For this study, an operator assumed the speech recognition
and behavior selector functions using a tele-operation
system (Wizard of Oz [23]) and followed pre-determinedAnswering children’s questions
Display

If the children asked the reader robot a question, it answers
with prepared explanation behaviors based on speech
recognition results from the operator. For this purpose, we
prepared ten explanation behaviors. For example, if a childasks, “what is a zucchini?” the robot answers: “it's a
cucumber-like vegetable.”L

5200 mm
P Parent L Listener robot
C Child R Reader robot

If the child leaves before the storytelling session is finished,
the reader robot asks him/her to return by calling by his/her
name.
After finishing the storytelling for each book, the reader
robot thanks the child for listening and announces that thestory hour is finished.
EXPERIMENT
Hypothesis and prediction: preferences

We predict that the presence of a listener robot will provide
positive storytelling effects for children. For example,
listening to conversations between robots enables theinteracting partners to understand the content more easily[24]. Another research reported that people are more
attracted to a dialogue between two robots than just amonologue from one robot [14]. These research works
mainly reported on the effects of two robots toward adultparticipants, but we believe that such effects might also
occur in child participants. Based on these considerations,
we made the following prediction:
Prediction 1: Children will prefer a storytelling situation
with both reader and listener robots compared tostorytelling only with a reader robot.
Hypothesis and prediction: speech activities

Moreover, we assume that the listener robot’s presence willchange the children’s speech activities during storytelling.
However, since the phenomena related to the number ofrobots and their roles remain basically unexplored andaccurately estimating young children’s behaviors is difficult,
we made two contradictory hypotheses about their effects
based on different theories and considerations.
Hypothesis about stimulating children’s speech activities
We assume that the presence of a listener robot during
storytelling will stimulate the children’s speech activities
and prompt them to ask more questions, because showing
conversations between robots enables interacting people tounderstand their contents more easily [24]. Moreover,asking behaviors by the listener robot might fuel thechildren’s curiosity about the story’s contents. In fact, apast work at an elementary school reported that when achild asked a robot questions, other they were stimulated to
ask additional questions themselves [25]. Based on these
considerations, we made the following prediction:

8120
mm

P

Requesting that a child return

FarewellR
C

Fig. 5 Experimental environment

Prediction 2-a: The presence of the listener robot willencourage the speech activities of children, i.e., morestatements and/or questions.
Hypothesis about satisfying children’s speech activities
We assume that observing conversations between reader
and listener robots will satisfy children’s speech activities,
and they will not ask the reader robot questions because thelistener robot had already asked them. The presence of thelistener robot might also change the role of the children
from addressees to side-participants; if the children feel thatthe reader robot is mainly talking to the listener robot, theymight behave less actively during the storytelling and focus
more on the robots’ conversations. Based on these
considerations, we made the following prediction:
Prediction 2-b: The presence of the listener robot will
suppress children’s speech activities, i.e., fewer statements
and/or questions.
Participants

Sixteen children (eight girls and eight boys from three tofive years old, average age 4.3, S.D 0.86) and their parents(15 mothers and 1 father) participated in the experiment.
Environment

Figure 5 shows the experiment environment. The room isapproximately 40 m2. Toys, books, and chairs are available
for the participants to represent a realistic playroom
environment; already this environment was used forexperiments in child-robot interaction research fields [26].
We placed reader and listener robots in front of the display
and a Kinect V2 behind it. The child sat on the floor to lookat the displayed picture book.
Condition

The study had a within-participants design with thefollowing two conditions:
One robot: In this condition, we only used the reader robot.
Without the listener robot, we didn’t use theasking/answering questions between the robots behaviors.
The gaze model did not consider the listener robot todetermine the reader robot’s gaze behaviors.
Two robots: In this condition, we used both the reader andlistener robots. All of the behaviors in the “Details ofimplemented behaviors” section were used during theexperiment. The gaze model considered the listener robot todecide the reader robot’s gaze behaviors.
Measurement

In this experiment, we measured one subjective item about
the preferences by directly asking to children after theexperiment which conditions they preferred. We alsomeasured the number of children’s utterances during thestorytelling to objectively investigate their speech activities
toward it.

These scenes suggest that the children are interested in boththe storytelling and/or the robots. On the other hand,children moved around during few seconds four times inboth conditions, seemingly distracted by toys or approachedtheir parents. After they started to move around, the system
detected their positions and then the reader robot asked
them to come back and listen to the story. They
immediately returned to the front of the display and listened
until it was over.

As supplemental measurements, their parents filled out aquestionnaire that consisted of three subjective items: thenaturalness of the reader robot gaze, their perceptions of
their child’s enjoyment, and their preferred condition (oneor two robots). The former two questionnaire items were
single scale, evaluated on a 1-to-7 point scale (7 is mostpositive), and the last was a binary choice between
conditions.
Procedure

Before the first session, the adult participants were given abrief description of our experiment’s purpose and procedure.
The first ten minutes were used to acclimatize the children
to the environment and the robots; during this period, thereader and listener robots greeted each other and talked.
Before the storytelling began, the child participant sat infront of the display, and the adult participant moved awayfrom her/his child.

Fig. 6 Child listened storytelling in the single condition

Since it had a within-participant design, each child sat
through two sessions of different conditions. The order ofthe conditions (one or two) and the picture books werecounterbalanced. After each session, the adult participantsfilled out a questionnaire. After the experiment, the adultand child participants separately answered questions about
their preferences to prevent bias.
The experimental protocol was approved by our
institutional review board (reference number 17-501-5)
RESULTS
General Trends

Fig. 7 Child pointing at a specific part of the display

In both conditions, in the typical interaction pattern, thechildren intently listened to the storytelling from the reader
robot (Fig. 6). Each child mainly changed their gaze targets
due to the timing of the changing situations of storytelling.
For example, when the reader robot started to talk, a childgenerally looked at it and then at the display. When thelistener robot asked a question, the child looked at it andthen at the reader robot and quietly listened to the story inboth conditions. Sometimes the child focused on a specificpart in a book’s picture when the listener robot asked aquestion (Fig. 7), e.g., approaching the display to examine
the ladybug after the listener robot asked about it.
We observed some atypical behaviors during theinteractions. For example, one girl stroked the heads of therobots or hugged them during the storytelling (Fig. 8).

Fig. 8 Girl hugging the robot during storytelling*14* : p < .05

Preferred number

12

One robot
Two robots

10

4.94 (0.36)
5.25 (0.27)

4.31 (0.37)
4.69 (0.43)

Preferred
number ofrobots8
7

Verification of Prediction 1

6
4

0
One robot

Two robots

Fig. 9 Number of robots preferred by children
2.50** : p < .05

2.00

Average

Children’s
enjoyment

Table 2 Questionnaire results from adult participants

8

2

1.50
1.00
0.50

One robot

Two robots

Fig. 10 Average number of children’s utterances

*

0.70

* : p < .05

0.60
0.50

Verification of Prediction 2

Fig. 10 and 11 show the average number of children’sutterances and their average number per minute. To verify
the activities of each condition, we conducted a paired t-test
for them. For the average number of children utterances, wefound a significant difference among the conditions (t(15) =2.179, p = .046, r = .49). For the average number ofchildren’s utterances per minute, we also found asignificant difference among the conditions (t(15) = 2.420,
p = .029, r = .53). These results indicate that the children
spoke less in the two-robot condition than in the one-robot
condition; prediction 2-b was supported.
We analyzed the children’s utterances during thestorytelling by separating them into two categories:
statements and questions. Two independent coders who did
not know our research hypothesis classified them (Table 1).
Their judgment matched reasonably well and yielded a
Cohen’s kappa coefficient of 0.726. We conducted a chisquared test, but there was no significant differences
between them (p=.011). No correlation between the numberof utterances and ages was observed in either condition.
As shown in Table 1, their utterances are mainly statements
in both conditions, e.g., a child said “a snail” when she saw
a picture of one during the storytelling. Some children
asked such questions as “what’s a zucchini?,” and then theoperator made appropriate responses with the preparedanswering behaviors.

0.40
0.30
0.20
0.10

Additional Analysis from Adult Participants

0.00
One robot

Two robots

Fig. 11 Average number per minute of children’s utterances

One robot
Two robots

Fig. 9 shows whether the children preferred one or two
robots in the conditions. Since one child could not decide
which condition she preferred, we eliminated that child. We
conducted a two-tailed binomial test and it indicated thatthe proportion of preferred number for two-robots conditionof 0.80 was higher than expected 0.50, p=.035 (2-tailed).
Therefore, prediction 1 was supported.

Analysis of Children’s Utterances

0.00

Average per minuteGazenaturalness

Statements

Questions

29
13

1
3

Table 1 Categorization of children’s utterances

Table 2 shows the questionnaire results from the adults.
First, to investigate whether our gaze model worked well inboth conditions, we conducted a paired t-test for feelings ofnaturalness about the reader robot’s gaze. The results
showed no significant differences between the conditions(t(15) = 1.232, p = .237, r = .30). Since the average valuesof this item at least exceeded the middle (four) in bothconditions, our developed gaze model seems to adequately
work regardless of the number of robots.

Next, to investigate how much the adults thought theirchildren enjoyed the storytelling, we conducted a paired ttest on their subjective feelings of the children’s enjoyment.
The results showed no significant differences between theconditions (t(15) = 1.065, p = .304, r = .27). A two-tailed
binomial test on the preferred condition metrics also
showed no significant differences (p=1.00) between
conditions; one adult could not decide which condition she
preferred. Thus, the preferences and the perceived
children's enjoyment did not completely match.
DISCUSSIONS
Design Implications

This study provides several implications. First, children
significantly preferred the two-robot condition over the
one-robot condition. This result shows a similar
phenomenon with adult participants that was reported inpast research [14]. Based on this study and past study, using
two robots would be useful to attract people to robot
contents regardless of the ages of the participants. Of course,
in reality using two robots increases installation costs. Our
experimental results provide evidence that can be used in
discussions about cost-benefit balances (a use of multiple
robots would be preferred by children but will be
expensive) with two robots for various services.
The next implication is the significant decrease in thechildren’s speech activities during storytelling with two
robots. We believe that this phenomenon has both positives
and negative effects on storytelling. For the positive aspect,decreasing the speech activities of children might focus
more of the children’s interest on the storytelling itself,
especially since the children in our study preferred the tworobot condition. We only investigated the effects of robots
with audiences comprised of a single child. But if this effectwere to appear in a situation where many children are
participating in storytelling, it might quietly attract themand reduce noisy situations. On the other hand, decreasing
their speech activities (including questions) might suppress
active participation in the storytelling. In other words,
children might just passively participate in the storytellingby observing the robot conversations. Appropriate
situations for using either a single or two robots forstorytelling might depend on particular purposes; e.g., if auser wants a child to actively participate in the storytelling,a single robot might be appropriate. If a user wants a childto quietly listen or the participation of many children, tworobots might be more appropriate.
Toward Autonomous Storytelling

In this study, we developed a semi-autonomousstorytelling-robot system to investigate the effects of alistener robot. One technical future work is to increase theautonomy of our storytelling system.
In this study, the operator controlled the speech recognition
functions. Because the success rate of current speech
recognition systems is only 21.3% [27] in realenvironments, children’s speech recognition remains
difficult [16]. Another problem is that children often ask
unpredictable or inexplicable questions. Since ignoringthem or offering dismissive answers would probably
discourage their interest in storytelling, we used a humanoperator as a speech recognizer. Past research also reported
that one operator might be able to control four or moremobile social robots in a shopping mall environment [28,29]. Therefore, we are optimistic that our semi-autonomous
approach is appropriate based on the limitations of current
technology and cost-efficiency issues.
Yet current technologies continue to have difficulty
accurately recognizing speech, as shown by iPhone’s Siriand Google speech recognition. The future growth of data
for training such systems will improve the performance ofspeech recognition for children. We need to gather more
speech data from children using robots; using tele-operated
robots is important for gathering additional data anddeveloping more autonomous systems.
Limitations

Since our experiment was conducted with our robot system
and its specific settings e.g., only using two robots,knowledge generality is limited. We cannot confirm
whether our finding about using two robots for storytelling
can be applied to other kinds of storytelling robots ordifferent contents. Moreover, since clearly measuring the
subjective impressions of such young children is difficult,more analysis with objective measurements is critical.
In our study, we did not compare a situation where both
robots act as readers, as in past research. Moreover, since
we used a listener robot that asks the reader robot questions,the information amount was different between conditions.
These facts should be addressed in discussion of our results.
In addition, we only compared the effects of different roles
by using robots, not focusing on people and/or virtual
agents. One interesting future work is to investigate theeffects of using different existence.
However, we believe that our setting is adequate to offer
knowledge for readers who are interested in child-robot
interaction and storytelling with two robots.
CONCLUSION

We developed a semi-autonomous storytelling-robot systemthat consists of a reader robot and a listener robot. For
natural storytelling behaviors, we developed a gaze model
to control the reader robot based on multi-party
conversation settings, including an object. To investigate
the effects of the listener robot on the preferences and theactivities of children, we conducted a within-participant
experiment where our robot system reads stories to children.
The experimental results showed that children preferredstorytelling with the listener robot more than without it.
Moreover, interestingly, their speech activities decreased
during storytelling with the listener robot. These results

would provide positive evidences to a use of multiple
robots for child-robot interaction.
Currently we are working about increasing autonomy of the
proposed system to deal with storytelling for multiple
children. We will investigate the effectiveness of the
proposed system towards more complex situations, andconsider comparisons between the multiple agents/people
for storytelling.
ACKNOWLEDGMENTS

This research work was supported by JSPS KAKENHI
Grant Numbers JP15H05322 and JP16K12505.
REFERENCES

1.

2.

3.

4.

5.

6.

7.

8.

9.

R. Isbell, J. Sobol, L. Lindauer, and A. Lowrance, “Theeffects of storytelling and story reading on the oral
language complexity and story comprehension ofyoung children,” Early childhood education journal,
vol. 32, no. 3, pp. 157-163, 2004.
F. Collins, “The use of traditional storytelling in
education to the learning of literacy skills,” Early Child
Development and Care, vol. 152, no. 1, pp. 77-108,
1999.
M. U. Bers, and J. Cassell, “Interactive storytellingsystems for children: Using technology to explore
language and identity,” Journal of Interactive Learning
Research, vol. 9, no. 2, pp. 183, 1998.
H. Alborzi, A. Druin, J. Montemayor, M. Platner, J.
Porteous, L. Sherman, A. Boltman, G. Taxén, J. Best,and J. Hammer, “Designing StoryRooms: interactive
storytelling spaces for children,” in Proceedings of the
3rd conference on Designing interactive systems:
processes, practices, methods, and techniques, pp. 95104, 2000.
J. A. Fails, A. Druin, and M. L. Guha, “Interactive
storytelling: Interacting with people, environment, andtechnology,” International Journal of Arts andTechnology, vol. 7, no. 1, pp. 112-124, 2014.
M. Fridin, “Storytelling by a kindergarten social
assistive robot: A tool for constructive learning inpreschool education,” Computers & education, vol. 70,
pp. 53-64, 2014.
J. Kory, and C. Breazeal, “Storytelling with robots:
Learning companions for preschool children's language
development,” in Robot and Human Interactive
Communication, 2014 RO-MAN: The 23rd IEEE
International Symposium on, pp. 643-648, 2014.
G. Gordon, S. Spaulding, J. Kory Westlund, J. J. Lee,
L. Plummer, M. Martinez, M. Das, and C. Breazeal,“Affective Personalization of a Social Robot Tutor forChildren’s Second Language Skills,” in Thirtieth
AAAI Conference on Artificial Intelligence, pp., 2016.
N. Fourati, A. Richard, S. Caillou, N. Sabouret, J.-C.
Martin, E. Chanoni, and C. Clavel, "Facial Expressionsof Appraisals Displayed by a Virtual Storyteller forChildren,"Intelligent
VirtualAgents:
16th
International Conference, IVA 2016, Los Angeles, CA,

USA, September 20–23, 2016, Proceedings, D. Traum,
W. Swartout, P. Khooshabeh et al., eds., pp. 234-244,
Cham: Springer International Publishing, 2016.
10. I. Leite, M. McCoy, M. Lohani, D. Ullman, N.
Salomons, C. Stokes, S. Rivers, and B. Scassellati,“Emotional Storytelling in the Classroom: Individual
versus Group Interaction between Children andRobots,” in Proceedings of the Tenth Annual
ACM/IEEE International Conference on Human-Robot
Interaction, Portland, Oregon, USA, pp. 75-82, 2015.
11. H. W. Park, M. Gelsomini, J. J. Lee, and C. Breazeal,“Telling Stories to Robots: The Effect of
Backchanneling on a Child's Storytelling,” inProceedings of the 2017 ACM/IEEE International
Conference on Human-Robot Interaction, Vienna,
Austria, pp. 100-108, 2017.
12. E. Goffman, Forms of talk: University of Pennsylvania
Press, 1981.
13. H. H. Clark, Using Language: Cambridge University
Press, 1996.
14. D. Sakamoto, K. Hayashi, T. Kanda, M. Shiomi, S.
Koizumi, H. Ishiguro, T. Ogasawara, and N. Hagita,“Humanoid Robots as a Broadcasting Communication
Medium in Open Public Spaces,” International Journalof Social Robotics, vol. 1, no. 2, pp. 157-169, 2009.
15. Z. Yumak, J. Ren, N. M. Thalmann, and J. Yuan,“Modelling multi-party interactions among virtual
characters,
robots,andhumans,”Presence:
Teleoperators and Virtual Environments, vol. 23, no. 2,
pp. 172-190, 2014.
16. J. Kennedy, v. Lemaignan, C. Montassier, P. Lavalade,
B. Irfan, F. Papadopoulos, E. Senft, and T. Belpaeme,“Child Speech Recognition in Human-Robot
Interaction: Evaluations and Recommendations,” inProceedings of the 2017 ACM/IEEE International
Conference on Human-Robot Interaction, Vienna,
Austria, pp. 82-90, 2017.
17. S. Bernardini, K. Porayska-Pomsta, and T. J. Smith,“ECHOES: An intelligent serious game for fosteringsocial communication in children with autism,”
Information Sciences, vol. 264, pp. 41-60, 2014.
18. L. P. E. Toh, A. Causo, P. W. Tzuo, I.-M. Chen, and S.
H. Yeo, “A Review on the Use of Robots in Education
and Young Children,” Educational Technology &Society, vol. 19, no. 2, pp. 148-163, 2016.
19. N. Karatas, S. Yoshikawa, P. R. S. De Silva, and M.
Okada, “Namida: Multiparty conversation based
driving agents in futuristic vehicle,” in International
Conference on Human-Computer Interaction, pp. 198207, 2015.
20. B. Mutlu, J. Forlizzi, and J. Hodgins, “A storytelling
robot: Modeling and evaluation of human-like gazebehavior,” in Humanoid robots, 2006 6th IEEE-RAS
international conference on, pp. 518-523, 2006.
21. B. Mutlu, T. Kanda, J. Forlizzi, J. Hodgins, and H.
Ishiguro, “Conversational gaze mechanisms forhumanlike robots,” ACM Transactions on InteractiveIntelligent Systems (TiiS), vol. 1, no. 2, pp. 12, 2012.
22. T. Komatsubara, M. Shiomi, T. Kanda, H. Ishiguro,
and N. Hagita, “Can a social robot help children's
understanding of science in classrooms?,” inProceedings of the second international conference on
Human-agent interaction, Tsukuba, Japan, pp. 83-90,
2014.
23. N. Dahlbäck, A. Jönsson, and L. Ahrenberg, “Wizardof Oz studies: why and how,” in Proceedings of the 1st
international conference on Intelligent user interfaces,
Orlando, Florida, USA, pp. 193-200, 1993.
24. T. Kanda, H. Ishiguro, T. Ono, M. Imai, and K. Mase,“Multi-robot
cooperationforhuman-robot
communication,” in Robot and Human Interactive
Communication, 2002. Proceedings. 11th IEEE
International Workshop on, pp. 271-276, 2002.
25. M. Shiomi, T. Kanda, I. Howley, K. Hayashi, and N.
Hagita, “Can a Social Robot Stimulate Science
Curiosity in Classrooms?,” International Journal ofSocial Robotics, vol. 7, no. 5, pp. 641-652, 2015.
26. M. Shiomi, and N. Hagita, “Social acceptance toward achildcare support robot system: web-based culturaldifferences investigation and a field study in Japan,”
Advanced Robotics, pp. 1-12, 2017.
27. M. Shiomi, D. Sakamoto, T. Kanda, C. T. Ishi, H.
Ishiguro, and N. Hagita, “Field Trial of a Networked
Robot at a Train Station,” International Journal ofSocial Robotics, vol. 3, no. 1, pp. 27-40, 2010.
28. D. F. Glas, T. Kanda, H. Ishiguro, and N. Hagita,“Field trial for simultaneous teleoperation of mobile
social robots,” in Proceedings of the 4th ACM/IEEE
international conference on Human robot interaction,
pp. 149-156, 2009.
29. M. Shiomi, T. Kanda, D. F. Glas, S. Satake, H.
Ishiguro, and N. Hagita, “Field trial of networked
social robots in a shopping mall,” in Intelligent Robots
and Systems, 2009. IROS 2009. IEEE/RSJ
International Conference on, pp. 2846-2853, 2009.