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Advances in computer processing power and emerging algorithms are allowing new ways of envisioning Human Computer Interaction. This paper focuses on the development of a computing algorithm that uses audio and visual sensors to detect and track a user's affective state to aid computer decision making. Using our Multi-stream Fused Hidden Markov Model(More)
This paper describes automatic speech recognition systems that satisfy two technological objectives. First, we seek to improve the automatic labeling of prosody, in order to aid future research in automatic speech understanding. Second, we seek to apply statistical speech recognition models of prosody for the purpose of reducing the word error rate of an(More)
Perhaps the most fundamental application of affective computing will be Human-Computer Interaction (HCI) in which the computer should have the ability to detect and track the user's affective states, and make corresponding feedback. The human multi-sensor affect system defines the expectation of multimodal affect analyzer. In this paper, we present our(More)
This paper presents an approach to automatically recognize emotion which children exhibit in an intelligent tutoring system. Emotion recognition can assist the computer agent to adapt its tutorial strategies to improve the efficiency of knowledge transmission. In this study, we detect three emotional classes: confidence, puzzle, and hesitation. Emotion is(More)
This paper computationalizes two linguistic concepts, contrast and focus, for the extraction of pragmatic and semantic salience from spontaneous speech. Contrast and focus have been widely investigated in modern linguistics, as categories that link intonation and information/discourse structure. This paper demonstrates the automatic tagging of contrast and(More)
This paper addresses the manual and automatic labeling, from spontaneous speech, of a particular type of user affect that we call the cognitive state in a tutorial dialogue system with students of primary and early middle school ages. Our definition of the cognitive state is based on analysis of children's spontaneous speech, which is acquired during(More)
Information extraction is a key component in dialogue systems. Knowledge about the world as well as knowledge specific to each word should be used for robust semantic processing. An intelligent agent is necessary for a dialogue system when meanings are strictly defined by using a world state model. A layered concept structure is proposed to represent(More)
Contrast is a very popular phenomenon in spoken language, and carries very important information to help understanding contents and structures of spoken language. In this paper, we propose an idea of automatic contrast detection as an effort for better speech understanding. We study the automatic tagging of three specific types of contrast: symmetric(More)
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