Assessing User Expertise in Spoken Dialog System Interactions

Eugenio Ribeiro; Fernando Batista; Isabel Trancoso; Jose Lopes; Ricardo Ribeiro; David de Matos

doi:10.1007/978-3-319-49169-1_24

Assessing User Expertise in Spoken Dialog System Interactions

Eugenio Ribeiro, Fernando Batista, Isabel Trancoso, Jose Lopes, Ricardo Ribeiro, David de Matos

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

Abstract

Identifying the level of expertise of its users is important for a system since it can lead to a better interaction through adaptation techniques. Furthermore, this information can be used in offline processes of root cause analysis. However, not much effort has been put into automatically identifying the level of expertise of an user, especially in dialog-based interactions. In this paper we present an approach based on a specific set of task related features. Based on the distribution of the features among the two classes – Novice and Expert – we used Random Forests as a classification approach. Furthermore, we used a Support Vector Machine classifier, in order to perform a result comparison. By applying these approaches on data from a real system, Let’s Go, we obtained preliminary results that we consider positive, given the difficulty of the task and the lack of competing approaches for comparison.

Original language	English
Title of host publication	Advances in Speech and Language Technologies for Iberian Languages
Subtitle of host publication	Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings
Editors	Alberto Abad, Alfonso Ortega, António Teixeira, Carmen García Mateo, Carlos D. Martínez Hinarejos, Fernando Perdigão, Fernando Batista, Nuno Mamede
Publisher	Springer Nature Switzerland AG
Pages	245-254
ISBN (Electronic)	978-3-319-49169-1
ISBN (Print)	978-3-319-49168-4
DOIs	https://doi.org/10.1007/978-3-319-49169-1_24
Publication status	Published - Nov 2016
Externally published	Yes
Event	International Conference on Advances in Speech and Language Technologies for Iberian Languages - Lisbon, Portugal Duration: 23 Nov 2016 → 25 Nov 2016 https://link.springer.com/conference/iberspeech

Publication series

Series	Lecture Notes in Computer Science
Volume	10077
ISSN	0302-9743

Conference

Conference	International Conference on Advances in Speech and Language Technologies for Iberian Languages
Abbreviated title	IberSPEECH 2016
Country	Portugal
City	Lisbon
Period	23/11/16 → 25/11/16
Internet address	https://link.springer.com/conference/iberspeech

Keywords

User expertise
Let’s Go
SVM
Random Forest

Access to Document

10.1007/978-3-319-49169-1_24

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Ribeiro, E., Batista, F., Trancoso, I., Lopes, J., Ribeiro, R., & de Matos, D. (2016). Assessing User Expertise in Spoken Dialog System Interactions. In A. Abad, A. Ortega, A. Teixeira, C. García Mateo, C. D. Martínez Hinarejos, F. Perdigão, F. Batista, & N. Mamede (Eds.), Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings (pp. 245-254). Springer Nature Switzerland AG. Lecture Notes in Computer Science Vol. 10077 https://doi.org/10.1007/978-3-319-49169-1_24

Ribeiro, Eugenio ; Batista, Fernando ; Trancoso, Isabel ; Lopes, Jose ; Ribeiro, Ricardo ; de Matos, David. / Assessing User Expertise in Spoken Dialog System Interactions. Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. editor / Alberto Abad ; Alfonso Ortega ; António Teixeira ; Carmen García Mateo ; Carlos D. Martínez Hinarejos ; Fernando Perdigão ; Fernando Batista ; Nuno Mamede. Springer Nature Switzerland AG, 2016. pp. 245-254 (Lecture Notes in Computer Science, Vol. 10077).

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abstract = "Identifying the level of expertise of its users is important for a system since it can lead to a better interaction through adaptation techniques. Furthermore, this information can be used in offline processes of root cause analysis. However, not much effort has been put into automatically identifying the level of expertise of an user, especially in dialog-based interactions. In this paper we present an approach based on a specific set of task related features. Based on the distribution of the features among the two classes – Novice and Expert – we used Random Forests as a classification approach. Furthermore, we used a Support Vector Machine classifier, in order to perform a result comparison. By applying these approaches on data from a real system, Let{\textquoteright}s Go, we obtained preliminary results that we consider positive, given the difficulty of the task and the lack of competing approaches for comparison.",

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Ribeiro, E, Batista, F, Trancoso, I, Lopes, J, Ribeiro, R & de Matos, D 2016, Assessing User Expertise in Spoken Dialog System Interactions. in A Abad, A Ortega, A Teixeira, C García Mateo, C D. Martínez Hinarejos, F Perdigão, F Batista & N Mamede (eds), Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. Springer Nature Switzerland AG, Lecture Notes in Computer Science, vol. 10077, pp. 245-254, International Conference on Advances in Speech and Language Technologies for Iberian Languages, Lisbon, Portugal, 23/11/16. https://doi.org/10.1007/978-3-319-49169-1_24

Assessing User Expertise in Spoken Dialog System Interactions. / Ribeiro, Eugenio; Batista, Fernando; Trancoso, Isabel; Lopes, Jose; Ribeiro, Ricardo; de Matos, David.

Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. ed. / Alberto Abad; Alfonso Ortega; António Teixeira; Carmen García Mateo; Carlos D. Martínez Hinarejos; Fernando Perdigão; Fernando Batista; Nuno Mamede. Springer Nature Switzerland AG, 2016. p. 245-254 (Lecture Notes in Computer Science, Vol. 10077).

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

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AB - Identifying the level of expertise of its users is important for a system since it can lead to a better interaction through adaptation techniques. Furthermore, this information can be used in offline processes of root cause analysis. However, not much effort has been put into automatically identifying the level of expertise of an user, especially in dialog-based interactions. In this paper we present an approach based on a specific set of task related features. Based on the distribution of the features among the two classes – Novice and Expert – we used Random Forests as a classification approach. Furthermore, we used a Support Vector Machine classifier, in order to perform a result comparison. By applying these approaches on data from a real system, Let’s Go, we obtained preliminary results that we consider positive, given the difficulty of the task and the lack of competing approaches for comparison.

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Ribeiro E, Batista F, Trancoso I, Lopes J, Ribeiro R, de Matos D. Assessing User Expertise in Spoken Dialog System Interactions. In Abad A, Ortega A, Teixeira A, García Mateo C, D. Martínez Hinarejos C, Perdigão F, Batista F, Mamede N, editors, Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. Springer Nature Switzerland AG. 2016. p. 245-254. (Lecture Notes in Computer Science, Vol. 10077). https://doi.org/10.1007/978-3-319-49169-1_24

Assessing User Expertise in Spoken Dialog System Interactions

Abstract

Publication series

Conference

Keywords

Access to Document

Rage: Realising an Applied Gaming Eco-system

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