@inproceedings{van-waterschoot-etal-2020-bliss,
title = "{BLISS}: An Agent for Collecting Spoken Dialogue Data about Health and Well-being",
author = {van Waterschoot, Jelte and
Hendrickx, Iris and
Khan, Arif and
Klabbers, Esther and
de Korte, Marcel and
Strik, Helmer and
Cucchiarini, Catia and
Theune, Mari{\"e}t},
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.57/",
pages = "449--458",
language = "eng",
ISBN = "979-10-95546-34-4",
abstract = "An important objective in health-technology is the ability to gather information about people`s well-being. Structured interviews can be used to obtain this information, but are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, though typically lack depth. In this paper, we present our first prototype of the BLISS agent, an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of Behaviour-based Language-Interactive Speaking Systems (BLISS) is to understand the motivations behind people`s happiness by conducting a personalized spoken dialogue based on a happiness model. We built our first prototype of the model to collect 55 spoken dialogues, in which the BLISS agent asked questions to users about their happiness and well-being. Apart from a description of the BLISS architecture, we also provide details about our dataset, which contains over 120 activities and 100 motivations and is made available for usage."
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<abstract>An important objective in health-technology is the ability to gather information about people‘s well-being. Structured interviews can be used to obtain this information, but are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, though typically lack depth. In this paper, we present our first prototype of the BLISS agent, an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of Behaviour-based Language-Interactive Speaking Systems (BLISS) is to understand the motivations behind people‘s happiness by conducting a personalized spoken dialogue based on a happiness model. We built our first prototype of the model to collect 55 spoken dialogues, in which the BLISS agent asked questions to users about their happiness and well-being. Apart from a description of the BLISS architecture, we also provide details about our dataset, which contains over 120 activities and 100 motivations and is made available for usage.</abstract>
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%0 Conference Proceedings
%T BLISS: An Agent for Collecting Spoken Dialogue Data about Health and Well-being
%A van Waterschoot, Jelte
%A Hendrickx, Iris
%A Khan, Arif
%A Klabbers, Esther
%A de Korte, Marcel
%A Strik, Helmer
%A Cucchiarini, Catia
%A Theune, Mariët
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G eng
%F van-waterschoot-etal-2020-bliss
%X An important objective in health-technology is the ability to gather information about people‘s well-being. Structured interviews can be used to obtain this information, but are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, though typically lack depth. In this paper, we present our first prototype of the BLISS agent, an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of Behaviour-based Language-Interactive Speaking Systems (BLISS) is to understand the motivations behind people‘s happiness by conducting a personalized spoken dialogue based on a happiness model. We built our first prototype of the model to collect 55 spoken dialogues, in which the BLISS agent asked questions to users about their happiness and well-being. Apart from a description of the BLISS architecture, we also provide details about our dataset, which contains over 120 activities and 100 motivations and is made available for usage.
%U https://aclanthology.org/2020.lrec-1.57/
%P 449-458
Markdown (Informal)
[BLISS: An Agent for Collecting Spoken Dialogue Data about Health and Well-being](https://aclanthology.org/2020.lrec-1.57/) (van Waterschoot et al., LREC 2020)
ACL
- Jelte van Waterschoot, Iris Hendrickx, Arif Khan, Esther Klabbers, Marcel de Korte, Helmer Strik, Catia Cucchiarini, and Mariët Theune. 2020. BLISS: An Agent for Collecting Spoken Dialogue Data about Health and Well-being. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 449–458, Marseille, France. European Language Resources Association.