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Automatic Emotion Recognition (AER) is an emerging research area in the Human-Computer Interaction (HCI) field. As Computers are becoming more and more popular every day, the study of interaction between humans (users) and computers is catching more attention. In order to have a more natural and friendly interface between humans and computers, it would be beneficial to give computers the ability to recognize situations the same way a human does. Equipped with an emotion recognition system, computers will be able to recognize their users' emotional states and show the appropriate reaction to…mehr

Produktbeschreibung
Automatic Emotion Recognition (AER) is an emerging research area in the Human-Computer Interaction (HCI) field. As Computers are becoming more and more popular every day, the study of interaction between humans (users) and computers is catching more attention. In order to have a more natural and friendly interface between humans and computers, it would be beneficial to give computers the ability to recognize situations the same way a human does. Equipped with an emotion recognition system, computers will be able to recognize their users' emotional states and show the appropriate reaction to that. In today's HCI systems, machines can recognize the speaker and also content of the speech, using speech recognition and speaker identification techniques. If machines are equipped with emotion recognition techniques, they can also know "how it is said" to react more appropriately, and make the interaction more natural. One of the most important human communication channels is the auditory channel which carries speech and vocal intonation. Therefore, in this book the speech signals are analyzed in order to set up an automatic system which recognizes the human emotional state.
Autorenporträt
Talieh received her MAS.c in Electrical and Computer Engineering in 2007 from Ryeron University, Toronto, Canada. Right now she is a research fellow at Centre for Pattern Analysis and Machine Intelligence (CPAMI)at University of Waterloo, Canada. Her areas of interest are Artificial Intelligence, Machine Learning, and Digital Signal Processing.