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The Tactical Language Training System helps learners acquire communicative competence in spoken Arabic and other languages. An intelligent agent coaches learners, assessing their mastery and providing tailored assistance. Learners then perform missions in an interactive story environment, where they communicate with autonomous, animated characters. Our(More)
Text-to-speech synthesis can play an important role in interactive education and training applications, as voices for animated agents. Such agents need high-quality voices capable of expressing intent and emotion. This paper presents preliminary results in an effort aimed at synthesizing expressive military speech for training applications. Such speech has(More)
The variability and reduction that are characteristic of talking in natural interaction make it very difficult to detect prominence in conversational speech. In this paper, we present analytic studies and automatic detection results for pitch accent, as well as on the realization of information structure phenomena like givenness and focus. For pitch accent,(More)
This work addresses the problem of optimal Wavelet packet (WP) filter bank decomposition based on the minimum probability of error signal representation (MPE-SR) principle. The problem is formulated as a complexity regularized optimization, where the tree-indexed structure of the WP family is explored to find conditions for reducing this problem to a type(More)
Emotional information in speech is commonly described in terms of prosody features such as F0, duration, and energy. In this paper, the focus is on how F0 characteristics can be used to effectively parametrize emotional quality in speech signals. Using an analysis-by-synthesis approach, F0 mean, range, and shape properties of emotional utterances are(More)
Narayanan and Jurafsky (1998) proposed that human language comprehension can be modeled by treating human comprehenders as Bayesian reasoners, and modeling the comprehension process with Bayesian decision trees. In this paper we extend the Narayanan and Jurafsky model to make further predictions about reading time given the probability of difference parses(More)