OpenEAR - Introducing the munich open-source emotion and affect recognition toolkit

• Published in: 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops pp. 1 - 6
• Main Authors: Eyben, F., Wollmer, M., Schuller, B.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2009
• Subjects: Automatic speech recognition; Emotion recognition; Engines; Feature extraction; Open source software; Software packages; Speech processing; Speech recognition
• ISBN: 9781424448005; 142444800X
• ISSN: 2156-8103
• DOI: 10.1109/ACII.2009.5349350

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.