Cloud Services for Culture Aware Conversation: Socially Assistive Robots and Virtual Assistants

Recchuto, Carmine; Gava, Luna; Grassi, Lucrezia; Grillo, Alberto; Lagomarsino, Marta; Lanza, Davide; Liu, Zijian; Papadopoulos, Chris; Papadopoulos, Irena; Scalmato, Antonello; Sgorbissa, Antonio

doi:10.1109/ur49135.2020.9144750

Cited by 17 publications

(8 citation statements)

References 15 publications

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“…Concerning the latter, a knowledge-based framework for culture-aware conversation has been developed: the system allows for letting the robot talk about a huge number of topics that may be more or less relevant for different cultures, by properly managing the flow of the conversation. The system, originally conceived for the humanoid robot Pepper, has been recently refactored as a portfolio of Cloud services [35,36].…”

Section: Culture and Roboticsmentioning

confidence: 99%

Towards Culture-Aware Co-Speech Gestures for Social Robots

Ariel

Recchiuto

Sgorbissa

2022

Int J of Soc Robotics

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Embedding social robots with the capability of accompanying their sentences with natural gestures may be the key to increasing their acceptability and their usage in real contexts. However, the definition of natural communicative gestures may not be trivial, since it strictly depends on the culture of the person interacting with the robot. The proposed work investigates the possibility of generating culture-dependent communicative gestures, by proposing an integrated approach based on a custom dataset composed exclusively of persons belonging to the same culture, an adversarial generation module based on speech audio features, a voice conversion module to manage the multi-person dataset, and a 2D-to-3D mapping module for generating three-dimensional gestures. The approach has eventually been implemented and tested with the humanoid robot Pepper. Preliminary results, obtained through a statistical analysis of the evaluations made by human participants identifying themselves as belonging to different cultures, are discussed.

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Section: Culture and Roboticsmentioning

confidence: 99%

Towards Culture-Aware Co-Speech Gestures for Social Robots

Ariel

Recchiuto

Sgorbissa

2022

Int J of Soc Robotics

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“…If the participant agrees that he/she likes Sumo Wrestling, the Experimental robot propagates this learning to also guess that he/she might also value other aspects of Japanese culture, whereas the Control Robot does not form such connections. A detailed explanation as to how the conversational interactions were developed and implemented during the trial stage has been previously described [24,25] The development of the CARESSES experimental and control robots required finding innovative technological solutions in order to embed the robots with the required Artificial Intelligence, enabling the robot to interact with the participants using its sensors and algorithms for data processing and reasoning. Indeed, the basic version of Pepper provides basic functionalities for interacting with people, but they need to be orchestrated through specific cognitive processes in order to enable a natural and engaging long-term interaction (given the aim was not to implement Wizard-of-Oz experiments but rather fully autonomous behaviour).…”

Section: Interventionsmentioning

confidence: 99%

The CARESSES Randomised Controlled Trial: Exploring the Health-Related Impact of Culturally Competent Artificial Intelligence Embedded Into Socially Assistive Robots and Tested in Older Adult Care Homes

Papadopoulos

Castro²,

Nigath

et al. 2021

Int J of Soc Robotics

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This trial represents the final stage of the CARESSES project which aimed to develop and evaluate a culturally competent artificial intelligent system embedded into social robots to support older adult wellbeing. A parallel group, single-blind randomised controlled trial was conducted across older adult care homes in England and Japan. Participants randomly allocated to the Experimental Group or Control Group 1 received a Pepper robot for up 18 h across 2 weeks. Two versions of the CARESSES artificial intelligence were tested: a fully culturally competent system (Experimental Group) and a more limited version (Control Group 1). Control Group 2 (Care As Usual) participants did not receive a robot. Quantitative outcomes of interest reported in the current paper were health-related quality of life (SF-36), loneliness (ULS-8), and perceptions of robotic cultural competence (CCATool-Robotics). Thirty-three residents completed all procedures. The difference in SF-36 Emotional Wellbeing scores between Experimental Group and Care As Usual participants over time was significant (F[1] = 6.614, sig = .019, ηp2 = .258), as was the comparison between Any Robot used and Care As Usual (F[1] = 5.128, sig = .031, ηp2 = .146). There were no significant changes in SF-36 physical health subscales. ULS-8 loneliness scores slightly improved among Experimental and Control Group 1 participants compared to Care As Usual participants, but this was not significant. This study brings new evidence which cautiously supports the value of culturally competent socially assistive robots in improving the psychological wellbeing of older adults residing in care settings.

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“…In the context of the project, a framework for autonomous, culturally competent conversation has been developed [10], [11]. The conversation framework can achieve mixed-initiative dialogues by exploiting the hierarchical structure of a Cultural Knowledge Base implemented as an OWL2 Ontology, thus enabling rich, knowledge-grounded conversations [12]. Being paralleled by a framework for probabilistic reasoning, such Ontology is designed to take into account the possible cultural differences between different users in a non-stereotyped way, and it stores chunks of sentences that can be composed in run-time, therefore enabling the system to talk about the aforementioned concepts in a culture-aware and engaging way [13] [14].…”

Section: Introductionmentioning

confidence: 99%

Knowledge Triggering, Extraction and Storage via Human-Robot Verbal Interaction

Grassi,

Recchiuto,

Sgorbissa

2021

Preprint

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This article describes a novel approach to expand in run-time the knowledge base of an Artificial Conversational Agent. A technique for automatic knowledge extraction from the user's sentence and four methods to insert the new acquired concepts in the knowledge base have been developed and integrated into a system that has already been tested for knowledge-based conversation between a social humanoid robot and residents of care homes. The run-time addition of new knowledge allows overcoming some limitations that affect most robots and chatbots: the incapability of engaging the user for a long time due to the restricted number of conversation topics. The insertion in the knowledge base of new concepts recognized in the user's sentence is expected to result in a wider range of topics that can be covered during an interaction, making the conversation less repetitive. Two experiments are presented to assess the performance of the knowledge extraction technique, and the efficiency of the developed insertion methods when adding several concepts in the Ontology.

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Cloud Services for Culture Aware Conversation: Socially Assistive Robots and Virtual Assistants

Cited by 17 publications

References 15 publications

Towards Culture-Aware Co-Speech Gestures for Social Robots

Towards Culture-Aware Co-Speech Gestures for Social Robots

The CARESSES Randomised Controlled Trial: Exploring the Health-Related Impact of Culturally Competent Artificial Intelligence Embedded Into Socially Assistive Robots and Tested in Older Adult Care Homes

Knowledge Triggering, Extraction and Storage via Human-Robot Verbal Interaction

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