@inproceedings{cherakara-etal-2023-furchat,
title = "{F}ur{C}hat: An Embodied Conversational Agent using {LLM}s, Combining Open and Closed-Domain Dialogue with Facial Expressions",
author = "Cherakara, Neeraj and
Varghese, Finny and
Shabana, Sheena and
Nelson, Nivan and
Karukayil, Abhiram and
Kulothungan, Rohith and
Afil Farhan, Mohammed and
Nesset, Birthe and
Moujahid, Meriam and
Dinkar, Tanvi and
Rieser, Verena and
Lemon, Oliver",
editor = "Stoyanchev, Svetlana and
Joty, Shafiq and
Schlangen, David and
Dusek, Ondrej and
Kennington, Casey and
Alikhani, Malihe",
booktitle = "Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue",
month = sep,
year = "2023",
address = "Prague, Czechia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.sigdial-1.55",
doi = "10.18653/v1/2023.sigdial-1.55",
pages = "588--592",
abstract = "We demonstrate an embodied conversational agent that can function as a receptionist and generate a mixture of open and closed-domain dialogue along with facial expressions, by using a large language model (LLM) to develop an engaging conversation. We deployed the system onto a Furhat robot, which is highly expressive and capable of using both verbal and nonverbal cues during interaction. The system was designed specifically for the National Robotarium to interact with visitors through natural conversations, providing them with information about the facilities, research, news, upcoming events, etc. The system utilises the state-of-the-art GPT-3.5 model to generate such information along with domain-general conversations and facial expressions based on prompt engineering.",
}
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<abstract>We demonstrate an embodied conversational agent that can function as a receptionist and generate a mixture of open and closed-domain dialogue along with facial expressions, by using a large language model (LLM) to develop an engaging conversation. We deployed the system onto a Furhat robot, which is highly expressive and capable of using both verbal and nonverbal cues during interaction. The system was designed specifically for the National Robotarium to interact with visitors through natural conversations, providing them with information about the facilities, research, news, upcoming events, etc. The system utilises the state-of-the-art GPT-3.5 model to generate such information along with domain-general conversations and facial expressions based on prompt engineering.</abstract>
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%0 Conference Proceedings
%T FurChat: An Embodied Conversational Agent using LLMs, Combining Open and Closed-Domain Dialogue with Facial Expressions
%A Cherakara, Neeraj
%A Varghese, Finny
%A Shabana, Sheena
%A Nelson, Nivan
%A Karukayil, Abhiram
%A Kulothungan, Rohith
%A Afil Farhan, Mohammed
%A Nesset, Birthe
%A Moujahid, Meriam
%A Dinkar, Tanvi
%A Rieser, Verena
%A Lemon, Oliver
%Y Stoyanchev, Svetlana
%Y Joty, Shafiq
%Y Schlangen, David
%Y Dusek, Ondrej
%Y Kennington, Casey
%Y Alikhani, Malihe
%S Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2023
%8 September
%I Association for Computational Linguistics
%C Prague, Czechia
%F cherakara-etal-2023-furchat
%X We demonstrate an embodied conversational agent that can function as a receptionist and generate a mixture of open and closed-domain dialogue along with facial expressions, by using a large language model (LLM) to develop an engaging conversation. We deployed the system onto a Furhat robot, which is highly expressive and capable of using both verbal and nonverbal cues during interaction. The system was designed specifically for the National Robotarium to interact with visitors through natural conversations, providing them with information about the facilities, research, news, upcoming events, etc. The system utilises the state-of-the-art GPT-3.5 model to generate such information along with domain-general conversations and facial expressions based on prompt engineering.
%R 10.18653/v1/2023.sigdial-1.55
%U https://aclanthology.org/2023.sigdial-1.55
%U https://doi.org/10.18653/v1/2023.sigdial-1.55
%P 588-592
Markdown (Informal)
[FurChat: An Embodied Conversational Agent using LLMs, Combining Open and Closed-Domain Dialogue with Facial Expressions](https://aclanthology.org/2023.sigdial-1.55) (Cherakara et al., SIGDIAL 2023)
ACL
- Neeraj Cherakara, Finny Varghese, Sheena Shabana, Nivan Nelson, Abhiram Karukayil, Rohith Kulothungan, Mohammed Afil Farhan, Birthe Nesset, Meriam Moujahid, Tanvi Dinkar, Verena Rieser, and Oliver Lemon. 2023. FurChat: An Embodied Conversational Agent using LLMs, Combining Open and Closed-Domain Dialogue with Facial Expressions. In Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 588–592, Prague, Czechia. Association for Computational Linguistics.