OpenEAR - Introducing the munich open-source emotion and affect recognition toolkit
Various open-source toolkits exist for speech recognition and speech processing. These toolkits have brought a great benefit to the research community, i.e. speeding up research. Yet, no such freely available toolkit exists for automatic affect recognition from speech. We herein introduce a novel op...
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Published in | 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops pp. 1 - 6 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.09.2009
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Subjects | |
Online Access | Get full text |
ISBN | 9781424448005 142444800X |
ISSN | 2156-8103 |
DOI | 10.1109/ACII.2009.5349350 |
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Summary: | Various open-source toolkits exist for speech recognition and speech processing. These toolkits have brought a great benefit to the research community, i.e. speeding up research. Yet, no such freely available toolkit exists for automatic affect recognition from speech. We herein introduce a novel open-source affect and emotion recognition engine, which integrates all necessary components in one highly efficient software package. The components include audio recording and audio file reading, state-of-the-art paralinguistic feature extraction and plugable classification modules. In this paper we introduce the engine and extensive baseline results. Pre-trained models for four affect recognition tasks are included in the openEAR distribution. The engine is tailored for multi-threaded, incremental on-line processing of live input in real-time, however it can also be used for batch processing of databases. |
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ISBN: | 9781424448005 142444800X |
ISSN: | 2156-8103 |
DOI: | 10.1109/ACII.2009.5349350 |