Bilyana Martinovski

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This paper presents a model for simulating cultural differences in the conversational behavior of virtual agents. The model provides parameters for differences in proxemics, gaze and overlap in turn taking. We present a review of literature on these factors and show results of a study where native speakers of North American English, Mexican Spanish and(More)
We present a new approach for rapidly developing dialogue capabilities for virtual humans. Starting from domain specification , an integrated authoring interface automatically generates dialogue acts with all possible contents. These dialogue acts are linked to example utterances in order to provide training data for natural language understanding and(More)
This paper reviews nine available transcription and annotation tools, considering in particular the special difficulties arising from transcribing and annotating multi-party, multi-modal dialogue. Tools are evaluated as to the ability to support the user's annotation scheme, ability to visualize the form of the data, compatibility with other tools,(More)
This paper describes the development of a multi-modal corpus based on multi-party multi-task driven common goal oriented spoken language interaction. The data consists of approximately 10 hours of audio human simulation radio data and nearly 5 hours of video and audio face-to-face sessions between human trainees and virtual agents.
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