A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Robots increasingly have the potential to interact with people in daily life. It is believed that, based on this ability, they will play an essential role in human society in the not-so-distant future. This article examined the proposition that robots could form relationships with children and that children might learn from robots as they learn from other children. In this article, this idea is studied in an 18-day field trial held at a Japanese elementary school. Two English-speaking "Robovie" robots interacted with first- and sixth-grade pupils at the perimeter of their respective classrooms. Using wireless identification tags and sensors, these robots identified and interacted with children who came near them. The robots gestured and spoke English with the children, using a vocabulary of about 300 sentences for speaking and 50 words for recognition. The children were given a brief picture-word matching English test at the start of the trial, after 1 week and after 2 weeks. Interactions were counted using the tags, and video and audio were recorded. In the majority of cases, a child's friends were present during the interactions. Interaction with the robot was frequent in the 1st week, and then it fell off sharply by the 2nd week. Nonetheless, some children continued to interact with the robot. Interaction time during the 2nd week predicted improvements in English skill at the posttest, controlling for pretest scores. Further analyses indicate that the robots may have been more successful in establishing common ground and influence when the children already had some initial proficiency or interest in English. These results suggest that interactive robots should be designed to have something in common with their users, providing a social as well as technical challenge. <s> BIB001 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Advancement in robotic research enables robot can assist human in many way. However, few researches have been done on applying on education. This paper reports field trials of using robot in an English learning classroom. In our experiment, the robot plays as a partner of a teacher. Five models of collaboration between teachers and robot are proposed. Teachers design the course flow in advance based on the learning content and these five models. Formative evaluations of the experiments are presented to show the impact of adopting robot in the classroom. <s> BIB002 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Interactive robots participating in our daily lives should have the fundamental ability to socially communicate with humans. In this paper, we propose a mechanism for two social communication abilities: forming long-term relationships and estimating friendly relationships among people. The mechanism for long-term relationships is based on three principles of behavior design. The robot we developed, Robovie, is able to interact with children in the same way as children do. Moreover, the mechanism is designed for long-term interaction along the following three design principles: (1) it calls children by name using radio frequency identification tags; (2) it adapts its interactive behaviors for each child based on a pseudo development mechanism; and (3) it confides its personal matters to the children who have interacted with the robot for an extended period of time. Regarding the estimation of friendly relationships, the robot assumes that people who spontaneously behave as a group together are friends. Then, by identifying each person in the interacting group around the robot, it estimates the relationships between them. We conducted a two-month field trial at an elementary school. An interactive humanoid robot, Robovie, was placed in a classroom at the school. The results of the field trial revealed that the robot successfully continued interacting with many children for two months, and seemed to have established friendly relationships with them. In addition, it demonstrated reasonable performance in identifying friendships among children. We believe that these results demonstrate the potential of current interactive robots to establish social relationships with humans in our daily lives. <s> BIB003 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> This paper introduces software which enables teachers create robot as a partner easily and find out how to help a teacher difficulties when using storytelling lessons. First of all, we must understand the relations between storytelling and language learning, and the benefit of a robot being the assistance of a teacher during the lesson. In the next step, let teachers use the "programming a robot into a storytelling tool" and design the "story time" during English class. According to the evaluation result, there was highly satisfied in the new system implementation and effectively improved teacher's organization and technique of difficulties in the storytelling lesson. In addition, tester also had the confidence to improve students' participation and atmosphere during the storytelling activities. <s> BIB004 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> As robot technologies develop, many researchers have tried to use robots to support education. Studies have shown that robots can help students develop problem-solving abilities and learn computer programming, mathematics, and science. However, few studies discuss the use of robots to facilitate the teaching of second languages. We discuss whether language teaching needs robot support, whether robots present an appropriate medium for language instruction, and what challenges must be overcome. In order to explore the possibility of using robots as an instructional tool for teaching a second language, this paper reviews prior studies concerning educational robots and analyzes the characteristics of robots and instructional media. Furthermore, we report on the design and testing of five instruction scenarios for teaching second language. Based on our empirical experience, we provide suggestions for future research directions in the realm of robots for language education. Keyword <s> BIB005 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Teaching is inherently a social interaction between teacher and student. Despite this knowledge, many educational tools, such as vocabulary training programs, still model the interaction in a tutoring scenario as unidirectional knowledge transfer rather than a social dialog. Therefore, ongoing research aims to develop virtual agents as more appropriate media in education. Virtual agents can induce the perception of a life-like social interaction partner that communicates through natural modalities such as speech, gestures and emotional expressions. This effect can be additionally enhanced with a physical robotic embodiment. This paper presents the development of social supportive behaviors for a robotic tutor to be used in a language learning application. The effect of these behaviors on the learning performance of students was evaluated. The results support that employing social supportive behavior increases learning efficiency of students. <s> BIB006 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> There is strong evidence that when two people talk to each other, they tend to converge, or align, on common ways of speaking (e.g., Pickering and Garrod, 2004). In this paper, we discuss possible mechanisms that might lead to linguistic alignment, contrasting mechanisms that are encapsulated within the language processing system, and so unmediated by beliefs about the interlocutor, with mechanisms that are mediated by beliefs about the interlocutor and that are concerned with considerations of either communicative success or social affect. We consider how these mechanisms might be implicated in human–computer interaction (HCI), and then review recent empirical studies that investigated linguistic alignment in HCI. We argue that there is strong evidence that alignment occurs in HCI, but that it differs in important ways from that found in interactions between humans: It is generally stronger and has a larger mediated component that is concerned with enhancing communicative success. <s> BIB007 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Various studies on robot assisted learning have proven them to be effective tools for language education because robots are remarkably successful in eliminating the affective filter. This study demonstrates ROBOSEM with class content for sustaining long-term interaction with students in English classes of elementary schools as a teaching assistant, not a teacher. We close with some practical considerations for the continuous process of improving technology and its diffusion throughout society, such as in elementary schools, through interviews with developers and observations from field trials. <s> BIB008 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> This study introduces the educational assistant robots that we developed for foreign language learning and explores the effectiveness of robot-assisted language learning (RALL) which is in its early stages. To achieve this purpose, a course was designed in which students have meaningful interactions with intelligent robots in an immersive environment. A total of 24 elementary students, ranging in age from ten to twelve, were enrolled in English lessons. A pre-test/post-test design was used to investigate the cognitive effects of the RALL approach on the students??? oral skills. No significant difference in the listening skill was found, but the speaking skills improved with a large effect size at the significance level of 0.01. Descriptive statistics and the pre-test/post-test design were used to investigate the affective effects of RALL approach. The result showed that RALL promoted and improved students??? satisfaction, interest, confidence, and motivation at the significance level of 0.01. <s> BIB009 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> There is an on-going study which aims to assist in teaching Sign Language (SL) to hearing impaired children by means of non-verbal communication and imitation based interaction games between a humanoid robot and the child. In this study, the robot will be able to express a word in SL among a set of chosen words using hand movements, body and face gestures. Having comprehended the word, the child will give relevant feedback to the robot. In the current study, we propose an interactive story telling game between a NAO H25 humanoid robot and preschool children based on Turkish Sign Language (TSL). Since most of the children do not know how to read and write, and they are not familiar with sign language, we prepared a short story including specially selected words which is performed by the robot verbally and with sign language as well. The children are expected to give feedback to the robot with matching colour flashcards when it implements a word in sign language. The robotic event covered 106 preschool children. The aim is to evaluate the children's sign language learning ability from a robot, and comparison of these results with the results of video based studies. <s> BIB010 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Early school years are an important period to lay out the foundation for learning a second language. In addition to mastering the basic language skills and keeping the learning process fun, promoting a lifelong learning habit should also be emphasised. Motivating elementary school students to learn English and avoiding misconceptions associated with the learning process are very important issues. This study attempted to explore the integration of book, computer and robot to create a novel and joyful English learning environment. Books are the most common learning media. If we can design a special mechanism linking books with digital learning content and a robot, students will be able to obtain supplementary learning content including motions performed by the robot to enhance learning outcomes. To implement this idea, a new learning system was designed and developed. Learning activities included vocabulary, single sentence read-along, full article read-along, conversation, sing-along and dancing. Cloze tests were implemented and the feasibility of the learning system was evaluated. Data collected from field observation and interviews were analysed. The results suggest that this system did enrich students' learning experience and enhance their motivation and engagement. <s> BIB011 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> In our research we advocate using game based scenarios for Robot Assisted Language Learning (RALL). We present two case studies that utilized such a methodology and also analyzed what constructs would have a pedagogical benefit. The constructs included various attributes such as, type of robot, location of learning, role of robot, role of teacher, etc. Our results showed that close linkages with existing curriculum reaped benefits and running RALL for small groups of children is the ideal case. We also reflect on how using game based scenarios for RALL resulted in higher motivation for the students. <s> BIB012 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Curiosity is key to learning, yet school children show wide variability in their eagerness to acquire information. Recent research suggests that other people have a strong influence on children’s exploratory behavior. Would a curious robot elicit children’s exploration and the desire to find out new things? In order to answer this question we designed a novel experimental paradigm in which a child plays an education tablet app with an autonomous social robot, which is portrayed as a younger peer. We manipulated the robot’s behavior to be either curiosity-driven or not and measured the child’s curiosity after the interaction. We show that some of the child’s curiosity measures are significantly higher after interacting with a curious robot, compared to a non-curious one, while others do not. These results suggest that interacting with an autonomous social curious robot can selectively guide and promote children’s curiosity. Categories and Subject Descriptors K.3.1 [Computers and Education]: Computer Uses in Education; I.2.9 [Artificial Intelligence]: Robotics <s> BIB013 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> This paper presents a design for a cutting-edge English program in which elementary school learners of English as a foreign language in Taiwan had lively interactions with a teaching assistant robot. Three dimensions involved in the design included (1) a pleasant and interactive classroom environment as the learning context, (2) a teaching assistant robot designed and built by the researchers as instructional technology (instructional tool/medium), and (3) the need for improved motivation and learning outcomes and positive learning experiences of the students as the core research problem. This Human–Robot Interaction (HRI) led to better pedagogical effects on learning and teaching by (1) employing a vivid, enjoyable teaching approach; (2) adopting practical, interesting learning materials; and (3) creating a natural, enjoyable learning context. Both quantitative and qualitative findings of this study indicate that the students' English learning experiences were enhanced, as were their motivation and learn... <s> BIB014 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> This study is to verify the effectiveness of robot TTS technology in assisting Korean English language learners to acquire a native-like accent by correcting the prosodic errors they commonly make. Child English language learners' F0 range, a prosodic variable, will be measured and analyzed for any changes in accent. We examined whether if robot with the currently available TTS technology appeared to be effective as much as a tele-presence robot with native speaker from the acoustic phonetic viewpoint. <s> BIB015 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Effective tutoring requires personalization of the interaction to each student. Continuous and efficient assessment of the student's skills are a prerequisite for such personalization. We developed a Bayesian active-learning algorithm that continuously and efficiently assesses a child's word-reading skills and implemented it in a social robot. We then developed an integrated experimental paradigm in which a child plays a novel story-creation tablet game with the robot. The robot is portrayed as a younger peer who wishes to learn to read, framing the assessment of the child's word-reading skills as well as empowering the child. We show that our algorithm results in an accurate representation of the child's word-reading skills for a large age range, 4-8 year old children, and large initial reading skill range. We also show that employing child-specific assessment-based tutoring results in an age- and initial reading skill-independent learning, compared to random tutoring. Finally, our integrated system enables us to show that implementing the same learning algorithm on the robot's reading skills results in knowledge that is comparable to what the child thinks the robot has learned. The child's perception of the robot's knowledge is age-dependent and may facilitate an indirect assessment of the development of theory-of-mind. <s> BIB016 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> This paper presents a study that aims to address the challenges of creating effective educational robots. To this end, we developed a social educational robot which acts as a peer that is also a learner of a foreign language rather than a tutor teaching it. Children engage in a game with a peer robot which is programmed to either always win or always lose. The purpose of this study is to investigate whether children would learn more if they were winning or losing the game to the robot. The study was conducted with 76 children aged 6–10 years old. The conducted study compares children's responses and children's improvements of English vocabulary after a game with the robot. Results indicate that children improve their English significantly more when playing with the losing robot. In addition, girls rated playing with the robot significantly higher than boys did regardless of the robot's playing strategy. <s> BIB017 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> An increasing amount of research is being conducted to determine how a robot tutor should behave socially in educational interactions with children. Both human-human and human-robot interaction literature predicts an increase in learning with increased social availability of a tutor, where social availability has verbal and nonverbal components. Prior work has shown that greater availability in the nonverbal behaviour of a robot tutor has a positive impact on child learning. This paper presents a study with 67 children to explore how social aspects of a tutor robot's speech influences their perception of the robot and their language learning in an interaction. Children perceive the difference in social behaviour between `low' and `high' verbal availability conditions, and improve significantly between a pre- and a post-test in both conditions. A longer-term retention test taken the following week showed that the children had retained almost all of the information they had learnt. However, learning was not affected by which of the robot behaviours they had been exposed to. It is suggested that in this short-term interaction context, additional effort in developing social aspects of a robot's verbal behaviour may not return the desired positive impact on learning gains. <s> BIB018 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Voice <s> Abstract Social robots are innovative new technologies that have considerable potential to support children’s education as tutors and learning companions. Given this potential, it behooves us to study the mechanisms by which children learn from social robots, as well as the similarities and differences between children’s learning from robots as compared to human partners. In the present study, we examined whether young children will attend to the same nonverbal social cues from a robot as from a human partner during a word learning task, specifically gaze and bodily orientation to an unfamiliar referent. Thirty-six children viewed images of unfamiliar animals with a human and with a robot. The interlocutor (human or robot) oriented toward, and provided names for, some of the animals, and children were given a posttest to assess their recall of the names. We found that children performed equally well on the recall test whether they had been provided with names by the robot or by the human. Moreover, in each case, their performance was constrained by the spatial distinctiveness of nonverbal orientation cues available to determine which animal was being referred to during naming. <s> BIB019
A robot may have either a synthetic voice or a pre-recorded voice. The exception is telepresence robots, which allow for the presence of a live speaker; hence, this section will focus on autonomous robots and teleoperated robots with voice capabilities. The use of synthetic voices is most common in RALL (e.g., References BIB013  BIB008 ). They are produced by text-to-speech (TTS) software, including Microsoft SDK BIB002 , Festival BIB012  , or the robot's native TTS module. Due to the flexibility in this method, the voices can have different identities (age, gender, language), and there can be considerable variation in the voices produced. This allows the robot to take on the voices of different characters, as sometimes used when telling a story BIB005 BIB014 BIB002 . This also allows purposeful exposure to varied voices and accents BIB005 BIB014 . That said, due to large variations in quality, students are not always satisfied with the voice produced BIB009 BIB006 . Furthermore, poor quality output may result in decreased language comprehension skills BIB009 and hinder correct prosody BIB015 . Although not tested, it is plausible that this will also affect pronunciation skills. An alternative to speech synthesis is to pre-record desired speech. This approach has been taken several times (e.g., References BIB017 BIB001 BIB010 ). Although not common, this output may be processed after recording, for example by pitch shifting an adult voice to make it sound child-like  BIB019 . Pre-recorded voices are advantageous in that they more readily carry emotion  . They may also be preferred for their ability to expose learners to naturalistic speech. As Rosenthal-von der Pütten, Strassmann, and Krämer found no difference in the extent to which people mimic a robot's word choice or word order when it uses TTS or pre-recorded voices  , this may mean that linguistic alignment will occur in other areas of speech as well. In fact, prosody and pause insertion are often aligned to conversational partners, even non-animate partners such as computers and virtual agents BIB007  , making the use of TTS potentially problematic in long-term language learning. However, one drawback to using natural speech, besides being more time-and labor-intensive to record, is that native speech is often fast. Kanda, Sato, Saiwaki, and Ishiguro, in reference to their 2004 study, suggested that they saw no significant increase in learning because the robot used a native English speaker's voice, and this may have been too fast and fluent for Japanese children with little prior exposure to the language to understand BIB003 . The benefits of using natural speech over TTS may be muted in the future, with the use of current and projected AI capabilities, such as those seen with Google's human sounding virtual assistant Duplex. It is unclear what identity robots' voices should project to influence optimal liking and learning. Sometimes, a voice is used that is similar to the students', such as using a child's voice when teaching children BIB016 BIB013 BIB010  . Kose and Yorganci reported that this had a "positive effect" on children BIB010 . This could be attributable to the age of the voice, the naturalness of the voice (prerecorded), or a combination, leading to enhanced common ground between the robot and student. Alternatively, the platform default voice may be used. It seems appropriate that the voice should match the intended social role of the robot (as teacher, peer, etc.) if there is one, but voice selection is a matter that requires further exploration. Nonetheless, it is recommended that the voice be as natural as possible, mimicking the prosody, rhythm, stress, intonation, and accent of a native speaker of the target language BIB009  BIB004 . Voice switching-switching from one voice to a distinctly different voice-might occur in a robot's storytelling mode, with robots that have both autonomous and telepresence capabilities, and with robots that can communicate in native and foreign languages. Park et al. handled this by having the robot say "Abracadabra" when changing its voice, so as not to confuse students BIB008 . Largely though, this is not addressed. How voice switching is viewed, including "perceptions of voice switching of multi-lingual robots[,] could be worth explicitly exploring in future work" BIB018 . Other factors influencing speech, such as volume and speaking rate, are sometimes adjustable BIB005 BIB002 . Rate of speech should be modifiable in at least some situations to suit users' needs BIB011 .