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Models of dialog state are important, both scientifically and practically, but today's best build strongly on tradition. This paper presents a new way to identify the important dimensions of dialog state, more bottom-up and empirical than previous approaches. Specifically, we applied Principal Component Analysis to a large number of low-level prosodic(More)
—In spoken dialog, speakers are simultaneously engaged in various mental processes, and it seems likely that the word that will be said next depends, to some extent, on the states of these mental processes. Further, these states can be inferred, to some extent, from properties of the speaker's voice as they change from moment to moment. As a illustration of(More)
People in dialog use a rich set of nonverbal behaviors, including variations in the prosody of their utterances. Such behaviors, often emotion-related, call for appropriate responses, but today's spoken dialog systems lack the ability to do this. Recent work has shown how to recognize user emotions from prosody and how to express system-side emotions with(More)
As a priority-setting exercise, we compared interactions between users and a simple spoken dialog system to interactions between users and a human operator. We observed usability events, places in which system behavior differed from human behavior, and for each we noted the impact, root causes, and prospects for improvement. We suggest some priority issues(More)
Patients with chronic low-back pain and depression were treated double blind with desipramine or doxepin. During this treatment several hypotheses regarding the modes of action of these drugs were examined. A low serotonin hypothesis was supported by the fact that patients who had pain relief following an acute challenge with fenfluramine, a relatively pure(More)
If we can model the cognitive and communicative processes underlying speech, we should be able to better predict what a speaker will do. With this idea as inspiration, we examine a number of prosodic and timing features as potential sources of information on what words the speaker is likely to say next. In spontaneous dialog we find that word probabilities(More)
Today there are solutions for some specific turn-taking problems , but no general model. We show how turn-taking can be reduced to two more general problems, prediction and selection. We also discuss the value of predicting not only future speech/silence but also prosodic features, thereby handing not only turn-taking but " turn-shaping ". To illustrate how(More)
Discovering and quantifying the prosodic signals that help manage turn-taking is difficult, in part because of the limitations of commonly used methods. This paper presents an integrated method that uses both perceptually-based analysis and quantitative analysis. The eight activities involved in the method — clarification of aims, problem formulation,(More)