Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics

Helen Hastie; Heriberto Cuayáhuitl; Nina Dethlefs; Simon Keizer; Xingkun Liu

doi:10.1007/978-981-10-2585-3_24

Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics

Helen Hastie^*, Heriberto Cuayáhuitl, Nina Dethlefs, Simon Keizer, Xingkun Liu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter

2 Citations (Scopus)

Abstract

In the past 10 years, very few published studies include some kind of extrinsic evaluation of an NLG component in an end-to-end-system, be it for phone or mobile-based dialogues or social robotic interaction. This may be attributed to the fact that these types of evaluations are very costly to set-up and run for a single component. The question therefore arises whether there is anything to be gained over and above intrinsic quality measures obtained in off-line experiments? In this article, we describe a case study of evaluating two variants of an NLG surface realiser and show that there are significant differences in both extrinsic measures and intrinsic measures. These differences can be used to inform further iterations of component and system development.

Original language	English
Title of host publication	Dialogues with Social Robots
Subtitle of host publication	Enablements, Analyses, and Evaluation
Editors	Kristiina Jokinen, Graham Wilcock
Publisher	Springer
Pages	303-311
Number of pages	9
Volume	Part V
ISBN (Electronic)	9789811025853
ISBN (Print)	9789811025846
DOIs	https://doi.org/10.1007/978-981-10-2585-3_24
Publication status	Published - 25 Dec 2016
Event	7th International Workshop on Spoken Dialogue Systems 2016 - Riekonlinna, Saariselkä, Finland Duration: 13 Jan 2016 → 16 Jan 2016

Publication series

Name	Lecture Notes in Electrical Engineering
Publisher	Springer
Volume	999
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	7th International Workshop on Spoken Dialogue Systems 2016
Abbreviated title	IWSDS 2016
Country/Territory	Finland
City	Saariselkä
Period	13/01/16 → 16/01/16

Keywords

Evaluation
Natural language generation
Spoken dialogue systems

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-981-10-2585-3_24

Cite this

Hastie, H., Cuayáhuitl, H., Dethlefs, N., Keizer, S., & Liu, X. (2016). Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics. In K. Jokinen, & G. Wilcock (Eds.), Dialogues with Social Robots: Enablements, Analyses, and Evaluation (Vol. Part V, pp. 303-311). (Lecture Notes in Electrical Engineering; Vol. 999). Springer. https://doi.org/10.1007/978-981-10-2585-3_24

Hastie, Helen ; Cuayáhuitl, Heriberto ; Dethlefs, Nina et al. / Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics. Dialogues with Social Robots: Enablements, Analyses, and Evaluation. editor / Kristiina Jokinen ; Graham Wilcock. Vol. Part V Springer, 2016. pp. 303-311 (Lecture Notes in Electrical Engineering).

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abstract = "In the past 10 years, very few published studies include some kind of extrinsic evaluation of an NLG component in an end-to-end-system, be it for phone or mobile-based dialogues or social robotic interaction. This may be attributed to the fact that these types of evaluations are very costly to set-up and run for a single component. The question therefore arises whether there is anything to be gained over and above intrinsic quality measures obtained in off-line experiments? In this article, we describe a case study of evaluating two variants of an NLG surface realiser and show that there are significant differences in both extrinsic measures and intrinsic measures. These differences can be used to inform further iterations of component and system development.",

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Hastie, H, Cuayáhuitl, H, Dethlefs, N, Keizer, S & Liu, X 2016, Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics. in K Jokinen & G Wilcock (eds), Dialogues with Social Robots: Enablements, Analyses, and Evaluation. vol. Part V, Lecture Notes in Electrical Engineering, vol. 999, Springer, pp. 303-311, 7th International Workshop on Spoken Dialogue Systems 2016, Saariselkä, Finland, 13/01/16. https://doi.org/10.1007/978-981-10-2585-3_24

Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics. / Hastie, Helen; Cuayáhuitl, Heriberto; Dethlefs, Nina et al.

Dialogues with Social Robots: Enablements, Analyses, and Evaluation. ed. / Kristiina Jokinen; Graham Wilcock. Vol. Part V Springer, 2016. p. 303-311 (Lecture Notes in Electrical Engineering; Vol. 999).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

TY - CHAP

T1 - Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics

AU - Hastie, Helen

AU - Cuayáhuitl, Heriberto

AU - Dethlefs, Nina

AU - Keizer, Simon

AU - Liu, Xingkun

PY - 2016/12/25

Y1 - 2016/12/25

N2 - In the past 10 years, very few published studies include some kind of extrinsic evaluation of an NLG component in an end-to-end-system, be it for phone or mobile-based dialogues or social robotic interaction. This may be attributed to the fact that these types of evaluations are very costly to set-up and run for a single component. The question therefore arises whether there is anything to be gained over and above intrinsic quality measures obtained in off-line experiments? In this article, we describe a case study of evaluating two variants of an NLG surface realiser and show that there are significant differences in both extrinsic measures and intrinsic measures. These differences can be used to inform further iterations of component and system development.

AB - In the past 10 years, very few published studies include some kind of extrinsic evaluation of an NLG component in an end-to-end-system, be it for phone or mobile-based dialogues or social robotic interaction. This may be attributed to the fact that these types of evaluations are very costly to set-up and run for a single component. The question therefore arises whether there is anything to be gained over and above intrinsic quality measures obtained in off-line experiments? In this article, we describe a case study of evaluating two variants of an NLG surface realiser and show that there are significant differences in both extrinsic measures and intrinsic measures. These differences can be used to inform further iterations of component and system development.

KW - Evaluation

KW - Natural language generation

KW - Spoken dialogue systems

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Hastie H, Cuayáhuitl H, Dethlefs N, Keizer S, Liu X. Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics. In Jokinen K, Wilcock G, editors, Dialogues with Social Robots: Enablements, Analyses, and Evaluation. Vol. Part V. Springer. 2016. p. 303-311. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-10-2585-3_24

Extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics

Abstract

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Keywords

ASJC Scopus subject areas

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