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首页> 外文会议>26th Annual German Conference on AI(Artificial Intelligence) KI 2003; Sep 15-18, 2003; Hamburg, Germany >Multimodal User State Recognition in a Modern Dialogue System
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Multimodal User State Recognition in a Modern Dialogue System

机译：现代对话系统中的多模式用户状态识别

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摘要

A new direction in improving automatic dialogue systems is to make a human-machine dialogue more similar to a human-human dialogue. A modern system should be able to recognize the semantic content of spoken utterances but also to interpret some paralinguistic or non-verbal information ―as indicators of the internal user state ―in order to detect success or trouble in communication. A common problem in a human-machine dialogue, where information about a users internal state of mind may give a clue, is, for instance, the recurrent misunderstanding of the user by the system. This can be prevented if we detect the anger in the users voice. In contrast to anger, a joyful face combined with a pleased voice may indicate a satisfied user, who wants to go on with the current dialogue behavior, while a hesitant searching gesture of the user reveals his unsureness. This paper explores the possibility of recognizing a user's internal state by using facial expression classification with eigenfaces and a prosodic classifier based on artificial neural networks combined with a discrete Hidden Markov Model (HMM) for gesture analysis in parallel. Our experiments show that all the three input modalities can be used to identify a users internal state. However, a user state is not always indicated by all three modalities at the same time; thus a fusion of the different modalities seems to be necessary. Different ways of modality fusion are discussed.
机译：改进自动对话系统的新方向是使人机对话更类似于人机对话。一个现代的系统应该能够识别语音的语义内容，而且能够解释某些副语言或非语言信息（作为内部用户状态的指示），以便检测通信的成败。在人机对话中，有关用户内部心理状态的信息可能会提供线索的常见问题是，例如，系统对用户的反复误解。如果我们在用户语音中检测到愤怒，则可以避免这种情况。与愤怒相反，喜怒无常的脸庞与令人愉悦的声音相结合，可能表示用户满意，他希望继续当前的对话行为，而用户犹豫的搜索手势则显示出他的不确定性。本文探讨了使用具有特征脸的面部表情分类和基于人工神经网络结合离散隐马尔可夫模型（HMM）进行并行手势分析的韵律分类器来识别用户内部状态的可能性。我们的实验表明，所有三种输入方式都可以用来识别用户的内部状态。但是，用户状态并非总是同时由所有三种模式指示的；因此，有必要融合不同的方式。讨论了形态融合的不同方式。

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