Title
An implementation of anger detection in speech signals
Author
TNO Defensie en Veiligheid
Mohamoud, A.A.
Maris, M.G.
Publication year
2008
Abstract
In this paper, an emotion classification system based on speech signals is presented. The classifier can identify the most common emotions, namely anger, neutral, happiness and fear. The algorithm computes a number of acoustic features which are fed into the classifier based on a pattern recognition approach. The classification system is of potential benefit for ambient intelligence in which the emotional and physical states of a person should be known to the intelligence of the environment. Using such information, the environment can better support humans in their daily activities in accordance with their preferences.
Subject
Emotions
Speech
Speech analysis
Emotions identification
Computer algorithms
Pattern recognition
Ambient intelligence
To reference this document use:
http://resolver.tudelft.nl/uuid:5411ad74-16c0-4207-a478-9466f1b45b4a
DOI
https://doi.org/10.1049/cp:20081111
TNO identifier
242593
Publisher
IET, London
ISBN
9780863418945
Source
4th International Conference on Intelligent Environments, IE 08, 21 - 22 July 2008, Seattle, WA.
Series
IET Conference Publications
Document type
conference paper