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ISCApad Archive  »  2010  »  ISCApad #148  »  Journals  »  EURASIP Journal on Advances in Signal Processing Special Issue on Emotion and Mental State Recognition from Speech

ISCApad #148

Sunday, October 10, 2010 by Chris Wellekens

7-2 EURASIP Journal on Advances in Signal Processing Special Issue on Emotion and Mental State Recognition from Speech
  

EURASIP Journal on Advances in Signal Processing  Special Issue on Emotion and Mental State Recognition from Speech 

 http://www.hindawi.com/journals/asp/si/emsr.html  _____________________________________________________ 
 As research in speech processing has matured, attention has shifted from linguistic-related applications such as speech recognition towards paralinguistic speech processing problems, in particular the recognition of speaker identity, language, emotion, gender, and age. Determination of emotion or mental state is a particularly challenging problem, in view of the significant variability in its expression posed by linguistic, contextual, and speaker-specific characteristics within speech.  Some of the key research problems addressed to date include isolating emotion-specific information in the speech signal, extracting suitable features, forming reduced-dimension feature sets, developing machine learning methods applicable to the task, reducing feature variability due to speaker and linguistic content, comparing and evaluating diverse methods, robustness, and constructing suitable databases. Automatic detection of other types of mental state, which share some characteristics with emotion, are also now being explored, for example, depression, cognitive load, and 'cognitive epistemic' states such as interest or skepticism.


Topics of interest in this special issue include, but are not limited to:
  * Signal processing methods for acoustic feature extraction in emotion recognition 
  * Robustness issues in emotion classification, including speaker and speaker group normalization and reduction of mismatch due to coding, noise, channel, and transmission effects
 * Applications of prosodic and temporal feature modeling in emotion recognition
 * Novel pattern recognition techniques for emotion recognition
 * Automatic detection of depression or psychiatric disorders from speech
 * Methods for measuring stress, emotion-related indicators, or cognitive load from speech
 * Studies relating speech production or perception to emotion and mental state recognition
 * Recognition of nonprototypical spontaneous and naturalistic emotion in speech
 * New methods for multimodal emotion recognition, where nonverbal speech content has a central role
 * Emotional speech synthesis research with clear implications for emotion recognition
 * Emerging research topics in recognition of emotion and mental state from speech
 * Novel emotion recognition systems and applications
 * Applications of emotion modeling to other related areas, for example, emotion-tolerant automatic speech recognition and recognition of nonlinguistic vocalizations
  Before submission authors should carefully read over the journal's Author Guidelines, which are located at
http://www.hindawi.com/journals/asp/guidelines.html. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable:  _____________________________________________________ 
Manuscript Due          August 1, 2010
First Round of Reviews  November 1, 2010
Publication Date        February 1, 2011

 _____________________________________________________   
Lead Guest Editor (for correspondence)

 _____________________________________________________ 
Julien Epps, The University of New South Wales, Australia;
National ICT Australia, Australia
Guest Editors
_____________________________________________________ 
Roddy Cowie, Queen's University Belfast, UK 
Shrikanth Narayanan, University of Southern California, USA 
Björn Schuller, Technische Universitaet Muenchen, Germany
Jianhua Tao, Chinese Academy of Sciences, China


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