This paper aims to find errors that lead to dialogue breakdowns in chat-oriented dialogue systems. We collected chat dialogue data, annotated them with dialogue breakdown labels, and collected comments describing the error that led to the breakdown. By mining the comments, we first identified error types. Then, we calculated the correlation between an error type and the degree of dialogue breakdown it incurred, quantifying its impact on dialogue breakdown. This is the first study to quantitatively analyze error types and their effect in chat-oriented dialogue systems.
This paper presents a taxonomy of errors in chat-oriented dialogue systems. Compared to human-human conversations and task-oriented dialogues, little is known about the errors made in chat-oriented dialogue systems. Through a data collection of chat dialogues and analyses of dialogue breakdowns, we classified errors and created a taxonomy. Although the proposed taxonomy may not be complete, this paper is the first to present a taxonomy of errors in chat-oriented dialogue systems. We also highlight the difficulty in pinpointing errors in such systems.
Seven cases are reported in which extravasation of contrast medium from the lateral lenticulostriate artery was observed on cerebral angiography performed in the early stage of hypertensive intracerebral hemorrhage.
We advance the theory that continuous bleeding from the ruptured artery with mechanical destruction and displacement of cerebral tissue is the cause of massive hematoma formation, and discuss the possibility of surgical treatment of the acute stage of hypertensive intracerebral hemorrhage.
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