In this book, a novel approach that combines speech-based
emotion recognition with adaptive human-computer dialogue modeling
is described. With the robust recognition of emotions from speech
signals as their goal, the authors analyze the effectiveness of
using a plain emotion recognizer, a speech-emotion recognizer
combining speech and emotion recognition, and multiple
speech-emotion recognizers at the same time. The semi-stochastic
dialogue model employed relates user emotion management to the
corresponding dialogue interaction history and allows the device to
adapt itself to the context, including altering the stylistic
realization of its speech. This comprehensive volume begins by
introducing spoken language dialogue systems and providing an
overview of human emotions, theories, categorization and emotional
speech. It moves on to cover the adaptive semi-stochastic dialogue
model and the basic concepts of speech-emotion recognition.
Finally, the authors show how speech-emotion recognizers can be
optimized, and how an adaptive dialogue manager can be implemented.
The book, with its novel methods to perform robust speech-based
emotion recognition at low complexity, will be of interest to a
variety of readers involved in human-computer interaction.
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