A computational model for the automatic recognition of affect in speech
A computational model for the automatic recognition of affect in speech
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ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
AVEC 2011-the first international audio/visual emotion challenge
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
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NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
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AVEC 2012: the continuous audio/visual emotion challenge
Proceedings of the 14th ACM international conference on Multimodal interaction
Proceedings of the 14th ACM international conference on Multimodal interaction
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Proceedings of the 14th ACM international conference on Multimodal interaction
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Proceedings of the 14th ACM international conference on Multimodal interaction
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COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
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Image and Vision Computing
Image and Vision Computing
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Recent developments in openSMILE, the munich open-source multimedia feature extractor
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Proceedings of the 3rd ACM international workshop on Audio/visual emotion challenge
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ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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Proceedings of the 15th ACM on International conference on multimodal interaction
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Journal of Visual Communication and Image Representation
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We introduce the openSMILE feature extraction toolkit, which unites feature extraction algorithms from the speech processing and the Music Information Retrieval communities. Audio low-level descriptors such as CHROMA and CENS features, loudness, Mel-frequency cepstral coefficients, perceptual linear predictive cepstral coefficients, linear predictive coefficients, line spectral frequencies, fundamental frequency, and formant frequencies are supported. Delta regression and various statistical functionals can be applied to the low-level descriptors. openSMILE is implemented in C++ with no third-party dependencies for the core functionality. It is fast, runs on Unix and Windows platforms, and has a modular, component based architecture which makes extensions via plug-ins easy. It supports on-line incremental processing for all implemented features as well as off-line and batch processing. Numeric compatibility with future versions is ensured by means of unit tests. openSMILE can be downloaded from http://opensmile.sourceforge.net/.