[Elsnet-list] Book Anouncement: Computational Paralinguistics
schuller at tum.de
Wed Mar 5 09:58:49 CET 2014
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
- 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.
- 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.
- The book:
- Table of Contents (pdf):
- Chapter01 (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
Machine Intelligence & Signal Processing Group
Institute for Human-Machine Communication
Technische Universität München
Munich / Germany
audEERING UG (limited)
Gilching / Germany
School of Computer Science and Technology
Harbin Institute of Technology
Harbin / P.R. China
Institute for Information and Communication Technologies
Graz / Austria
Centre Interfacultaire en Sciences Affectives
Université de Genève
Geneva / Switzerland
schuller at ieee.org<mailto:schuller at ieee.org>
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