Causal analysis of task completion errors in spoken music retrieval interactions
Sunao Hara, Norihide Kitaoka, Kazuya Takeda · 2012
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.