|
Dear List, Hoping it may be of interest to some of you, let us announce a new book that is now available focussing entirely on Computational Paralinguistics: Björn Schuller, Anton Batliner Computational Paralinguistics: Emotion, Affect and Personality in Speech and Language Processing Wiley, ISBN: 978-1-119-97136-8, 344 pages, November 2013 Description - This book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (‘paralinguistics’) expressed by or embedded in human
speech and language. - It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into
account recent developments within speech signal processing, machine intelligence and data mining. - Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: - Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art engineering approaches for speech signal processing and machine intelligence. - Explains the history and state of the art of all of the sub-fields which contribute to the topic of computational paralinguistics. - Covers the signal processing and machine learning aspects of the actual computational modelling of emotion and personality and explains the detection process from corpus collection to feature extraction and from model testing to system
integration. - Details aspects of real-world system integration including distribution, weakly supervised learning and confidence measures. - Outlines machine learning approaches including static, dynamic and context-sensitive algorithms for classification and regression. - Includes a tutorial on freely available toolkits, such as the open-source ‘openEAR’ toolkit for emotion and affect recognition co-developed by one of the authors, and a listing of standard databases and feature sets used in the field
to allow for immediate experimentation enabling the reader to build an emotion detection model on an existing corpus. Links: - The book: http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119971365.html - Table of Contents (pdf): http://media.wiley.com/product_data/excerpt/65/11199713/1119971365-16.pdf - Chapter01 (pdf): http://media.wiley.com/product_data/excerpt/65/11199713/1119971365-14.pdf Thanks and best wishes, Björn Schuller and Anton Batliner ___________________________________________ PD Dr.-Ing. habil. DI univ. Björn W. Schuller Senior Lecturer in Machine Learning Department of Computing Imperial College London London / UK Head Machine Intelligence & Signal Processing Group Institute for Human-Machine Communication Technische Universität München Munich / Germany CEO audEERING UG (limited) Gilching / Germany Visiting Professor School of Computer Science and Technology Harbin Institute of Technology Harbin / P.R. China Associate Institute for Information and Communication Technologies Joanneum Research Graz / Austria Associate Centre Interfacultaire en Sciences Affectives
Université de Genève Geneva / Switzerland ___________________________________________ This message is confidential. It may also be privileged or otherwise protected by work product immunity or other legal rules. If you have received it by mistake please let us know by reply and then delete it from your system; you should
not copy it or disclose its contents to anyone. All messages sent to and from our institute may be monitored to ensure compliance with internal policies and to protect our business. Emails are not secure and cannot be guaranteed to be error free as they can
be intercepted, amended, lost or destroyed, or contain viruses. Anyone who communicates with us by email is taken to accept these risks. |