BLISS: An agent for collecting spoken dialogue data about health and well-being

Jelte van Waterschoot; Iris Hendrickx; Arif Khan; Esther Klabbers; Marcel de Korte; Helmer Strik; Catia Cucchiarini; Mariët Theune

BLISS: An agent for collecting spoken dialogue data about health and well-being

Jelte van Waterschoot^*, Iris Hendrickx, Arif Khan, Esther Klabbers, Marcel de Korte, Helmer Strik, Catia Cucchiarini, Mariët Theune

^*Corresponding author for this work

Human Media Interaction

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

8 Citations (Scopus)

60 Downloads (Pure)

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 these are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, yet they typically lack depth. In this paper, we present our first prototype of the Behaviour-based Language-Interactive Speaking Systems (BLISS), an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of 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 mentions of over 120 activities and 100 motivations and is made available for usage.

Original language	English
Title of host publication	Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020)
Editors	Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Publisher	European Language Resources Association (ELRA)
Pages	449-458
Number of pages	10
ISBN (Electronic)	9791095546344
Publication status	Published - 2020
Event	12th Language Resources and Evaluation Conference, LREC 2020 - Palais du Pharo, Marseille, France Duration: 11 May 2020 → 16 May 2020 Conference number: 12 https://lrec2020.lrec-conf.org/en/

Conference

Conference	12th Language Resources and Evaluation Conference, LREC 2020
Abbreviated title	LREC
Country/Territory	France
City	Marseille
Period	11/05/20 → 16/05/20
Internet address	https://lrec2020.lrec-conf.org/en/

Keywords

Conversational
Happiness model
Healthcare
Natural language generation
Spoken dialogue system
Spoken Dutch

Access to Document

2020.lrec-1.57Final published version, 1.02 MBLicence: CC BY-NC

Cite this

van Waterschoot, J., Hendrickx, I., Khan, A., Klabbers, E., de Korte, M., Strik, H., Cucchiarini, C., & Theune, M. (2020). BLISS: An agent for collecting spoken dialogue data about health and well-being. In N. Calzolari, F. Bechet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020) (pp. 449-458). European Language Resources Association (ELRA).

van Waterschoot, Jelte ; Hendrickx, Iris ; Khan, Arif et al. / BLISS: An agent for collecting spoken dialogue data about health and well-being. Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020). editor / Nicoletta Calzolari ; Frederic Bechet ; Philippe Blache ; Khalid Choukri ; Christopher Cieri ; Thierry Declerck ; Sara Goggi ; Hitoshi Isahara ; Bente Maegaard ; Joseph Mariani ; Helene Mazo ; Asuncion Moreno ; Jan Odijk ; Stelios Piperidis. European Language Resources Association (ELRA), 2020. pp. 449-458

@inproceedings{5000dc1fdb31441fa695b74290b844ba,

title = "BLISS: An agent for collecting spoken dialogue data about health and well-being",

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 these are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, yet they typically lack depth. In this paper, we present our first prototype of the Behaviour-based Language-Interactive Speaking Systems (BLISS), an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of 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 mentions of over 120 activities and 100 motivations and is made available for usage.",

keywords = "Conversational, Happiness model, Healthcare, Natural language generation, Spoken dialogue system, Spoken Dutch",

author = "{van Waterschoot}, Jelte and Iris Hendrickx and Arif Khan and Esther Klabbers and {de Korte}, Marcel and Helmer Strik and Catia Cucchiarini and Mari{\"e}t Theune",

year = "2020",

language = "English",

pages = "449--458",

editor = "Nicoletta Calzolari and Frederic Bechet and Philippe Blache and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis",

booktitle = "Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020)",

publisher = "European Language Resources Association (ELRA)",

note = "12th Language Resources and Evaluation Conference, LREC 2020, LREC ; Conference date: 11-05-2020 Through 16-05-2020",

url = "https://lrec2020.lrec-conf.org/en/",

}

van Waterschoot, J, Hendrickx, I, Khan, A, Klabbers, E, de Korte, M, Strik, H, Cucchiarini, C & Theune, M 2020, BLISS: An agent for collecting spoken dialogue data about health and well-being. in N Calzolari, F Bechet, P Blache, K Choukri, C Cieri, T Declerck, S Goggi, H Isahara, B Maegaard, J Mariani, H Mazo, A Moreno, J Odijk & S Piperidis (eds), Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020). European Language Resources Association (ELRA), pp. 449-458, 12th Language Resources and Evaluation Conference, LREC 2020, Marseille, France, 11/05/20.

BLISS: An agent for collecting spoken dialogue data about health and well-being. / van Waterschoot, Jelte; Hendrickx, Iris; Khan, Arif et al.
Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020). ed. / Nicoletta Calzolari; Frederic Bechet; Philippe Blache; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Helene Mazo; Asuncion Moreno; Jan Odijk; Stelios Piperidis. European Language Resources Association (ELRA), 2020. p. 449-458.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - BLISS: An agent for collecting spoken dialogue data about health and well-being

AU - van Waterschoot, Jelte

AU - Hendrickx, Iris

AU - Khan, Arif

AU - Klabbers, Esther

AU - de Korte, Marcel

AU - Strik, Helmer

AU - Cucchiarini, Catia

AU - Theune, Mariët

N1 - Conference code: 12

PY - 2020

Y1 - 2020

N2 - 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 these are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, yet they typically lack depth. In this paper, we present our first prototype of the Behaviour-based Language-Interactive Speaking Systems (BLISS), an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of 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 mentions of over 120 activities and 100 motivations and is made available for usage.

AB - 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 these are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, yet they typically lack depth. In this paper, we present our first prototype of the Behaviour-based Language-Interactive Speaking Systems (BLISS), an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of 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 mentions of over 120 activities and 100 motivations and is made available for usage.

KW - Conversational

KW - Happiness model

KW - Healthcare

KW - Natural language generation

KW - Spoken dialogue system

KW - Spoken Dutch

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M3 - Conference contribution

AN - SCOPUS:85096568162

SP - 449

EP - 458

BT - Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020)

A2 - Calzolari, Nicoletta

A2 - Bechet, Frederic

A2 - Blache, Philippe

A2 - Choukri, Khalid

A2 - Cieri, Christopher

A2 - Declerck, Thierry

A2 - Goggi, Sara

A2 - Isahara, Hitoshi

A2 - Maegaard, Bente

A2 - Mariani, Joseph

A2 - Mazo, Helene

A2 - Moreno, Asuncion

A2 - Odijk, Jan

A2 - Piperidis, Stelios

PB - European Language Resources Association (ELRA)

T2 - 12th Language Resources and Evaluation Conference, LREC 2020

Y2 - 11 May 2020 through 16 May 2020

ER -

van Waterschoot J, Hendrickx I, Khan A, Klabbers E, de Korte M, Strik H et al. BLISS: An agent for collecting spoken dialogue data about health and well-being. In Calzolari N, Bechet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, editors, Proceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020). European Language Resources Association (ELRA). 2020. p. 449-458

BLISS: An agent for collecting spoken dialogue data about health and well-being

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