@InBook{HaqJackson_MachineAudition10,
  author = 	{Haq, S. and Jackson, P.J.B.},
  title = 	{Machine Audition: Principles, Algorithms and Systems},
  chapter = 	{Multimodal Emotion Recognition},
  publisher = 	{IGI Global},
  address =	{Hershey PA},
  year = 	{2010},
  month = 	{Aug.},
  editor = 	{Wang, W.},
  pages = 	{398-423},
  abstract = 
"Recent advances in human-computer interaction technology go beyond 
the successful transfer of data between human and machine by seeking 
to improve the naturalness and friendliness of user interactions. An 
important augmentation, and potential source of feedback, comes from 
recognizing the user‘s expressed emotion or affect. This chapter 
presents an overview of research efforts to classify emotion using 
different modalities: audio, visual and audio-visual combined. 
Theories of emotion provide a framework for defining emotional 
categories or classes. The first step, then, in the study of human 
affect recognition involves the construction of suitable databases. 
The authorsdescribe fifteen audio, visual and audio-visual data sets, 
and the types of feature that researchers have used to represent the 
emotional content. They discuss data-driven methods of feature 
selection and reduction, which discard noise and irrelevant 
information to maximize the concentration of useful information. 
They focus on the popular types of classifier that are used to 
decide to which emotion class a given example belongs, and methods 
of fusing information from multiple modalities. Finally, the authors 
point to some interesting areas for future investigation in this 
field, and conclude."
}
% ISBN-13: 978-1615209194
% DOI: 10.4018/978-1-61520-919-4
% http://www.igi-global.com/Bookstore/Chapter.aspx?TitleId=45495