Advances in Natural Multimodal Dialogue Systems (Text, by Jan van Kuppevelt, Laila Dybkjær, Niels Ole Bernsen

By Jan van Kuppevelt, Laila Dybkjær, Niels Ole Bernsen

The most subject of this quantity is typical multimodal interplay. The e-book is exclusive in that it brings jointly an outstanding many contributions concerning features of ordinary and multimodal interplay written through some of the vital actors within the box. subject matters addressed comprise speaking heads, conversational brokers, tutoring structures, multimodal conversation, desktop studying, architectures for multimodal discussion structures, platforms review, and knowledge annotation.

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Advances in Natural Multimodal Dialogue Systems (Text, Speech and Language Technology)

The most subject of this quantity is ordinary multimodal interplay. The booklet is exclusive in that it brings jointly a very good many contributions concerning elements of common and multimodal interplay written by means of the various vital actors within the box. subject matters addressed comprise speaking heads, conversational brokers, tutoring structures, multimodal conversation, computer studying, architectures for multimodal discussion structures, structures review, and knowledge annotation.

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Extra info for Advances in Natural Multimodal Dialogue Systems (Text, Speech and Language Technology)

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REA has a fully articulated graphical body, can sense the user passively through cameras and audio input, and is capable of speech with intonation, facial display, and gestural output. The system currently consists of a large projection screen on which REA is displayed and which the user stands in front of. Two cameras mounted on top of the projection screen track the user’s head and hand positions in space. Users wear a microphone for capturing speech input. A single SGI Octane computer runs the graphics and conversation engine of REA, while several other computers manage the speech recognition and generation and image processing.

During the interview, REA asked subjects how much they were able to pay for an apartment; subjects’ responses were entered as $X per month. 5 X), and mentioned that the price was negotiable. On the questionnaire, subjects were asked how much they would be willing to pay for the second apartment, and this was encoded as Z. The task measure used was (Z - X) / (Y - X), which varies from 0% if the user did not budge from their original requested price, to 100% if they offered the full asking price.

But, does small talk produced by an ECA in a sales encounter actually build trust and solidarity with users? And, does nonverbal behaviour play the same critical role in human-ECA social dialogue as it appears to play in human-human social interactions? In order to answer these questions, we conducted an empirical study in which subjects were interviewed by REA about their housing needs, shown two “virtual” apartments, and then asked to submit a bid on one of them. For the purpose of the experiment, REA was controlled by a human wizard and followed scripts identical to the output of the planner (but faster, and not dependent on automatic speech recognition or computational vision).

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