@inproceedings{hara-etal-2012-causal,
title = "Causal analysis of task completion errors in spoken music retrieval interactions",
author = "Hara, Sunao and
Kitaoka, Norihide and
Takeda, Kazuya",
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
month = may,
year = "2012",
address = "Istanbul, Turkey",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/1059_Paper.pdf",
pages = "1365--1372",
abstract = "In this paper, we analyze the causes of task completion errors in spoken dialog systems, using a decision tree with N-gram features of the dialog to detect task-incomplete dialogs. The dialog for a music retrieval task is described by a sequence of tags related to user and system utterances and behaviors. The dialogs are manually classified into two classes: completed and uncompleted music retrieval tasks. Differences in tag classification performance between the two classes are discussed. We then construct decision trees which can detect if a dialog finished with the task completed or not, using information gain criterion. Decision trees using N-grams of manual tags and automatic tags achieved 74.2{\%} and 80.4{\%} classification accuracy, respectively, while the tree using interaction parameters achieved an accuracy rate of 65.7{\%}. We also discuss more details of the causality of task incompletion for spoken dialog systems using such trees.",
}
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%0 Conference Proceedings
%T Causal analysis of task completion errors in spoken music retrieval interactions
%A Hara, Sunao
%A Kitaoka, Norihide
%A Takeda, Kazuya
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 may
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F hara-etal-2012-causal
%X In this paper, we analyze the causes of task completion errors in spoken dialog systems, using a decision tree with N-gram features of the dialog to detect task-incomplete dialogs. The dialog for a music retrieval task is described by a sequence of tags related to user and system utterances and behaviors. The dialogs are manually classified into two classes: completed and uncompleted music retrieval tasks. Differences in tag classification performance between the two classes are discussed. We then construct decision trees which can detect if a dialog finished with the task completed or not, using information gain criterion. Decision trees using N-grams of manual tags and automatic tags achieved 74.2% and 80.4% classification accuracy, respectively, while the tree using interaction parameters achieved an accuracy rate of 65.7%. We also discuss more details of the causality of task incompletion for spoken dialog systems using such trees.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/1059_Paper.pdf
%P 1365-1372
Markdown (Informal)
[Causal analysis of task completion errors in spoken music retrieval interactions](http://www.lrec-conf.org/proceedings/lrec2012/pdf/1059_Paper.pdf) (Hara et al., LREC 2012)
ACL