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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 8th International Conference on Language Resources and Evaluation, LREC 2012 |
| Publisher | European Language Resources Association (ELRA) |
| Pages | 1365-1372 |
| Number of pages | 8 |
| ISBN (Electronic) | 9782951740877 |
| Publication status | Published - Jan 1 2012 |
| Externally published | Yes |
| Event | 8th International Conference on Language Resources and Evaluation, LREC 2012 - Istanbul, Turkey Duration: May 21 2012 → May 27 2012 |
Other
| Other | 8th International Conference on Language Resources and Evaluation, LREC 2012 |
|---|---|
| Country | Turkey |
| City | Istanbul |
| Period | 5/21/12 → 5/27/12 |
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Keywords
- Interaction parameters
- Spoken dialog
- Task incompletion
ASJC Scopus subject areas
- Linguistics and Language
- Language and Linguistics
- Education
- Library and Information Sciences
Cite this
Causal analysis of task completion errors in spoken music retrieval interactions. / Hara, Sunao; Kitaoka, Norihide; Takeda, Kazuya.
Proceedings of the 8th International Conference on Language Resources and Evaluation, LREC 2012. European Language Resources Association (ELRA), 2012. p. 1365-1372.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Causal analysis of task completion errors in spoken music retrieval interactions
AU - Hara, Sunao
AU - Kitaoka, Norihide
AU - Takeda, Kazuya
PY - 2012/1/1
Y1 - 2012/1/1
N2 - 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.
AB - 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.
KW - Interaction parameters
KW - Spoken dialog
KW - Task incompletion
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M3 - Conference contribution
SP - 1365
EP - 1372
BT - Proceedings of the 8th International Conference on Language Resources and Evaluation, LREC 2012
PB - European Language Resources Association (ELRA)
ER -