Machot et al 2011a - Revision history

Scipediacontent at 12:44, 21 January 2021

2021-01-21T12:44:48Z

Scipediacontent: Scipediacontent moved page Draft Content 696191418 to Machot et al 2011a

2020-10-14T12:59:44Z

Scipediacontent moved page Draft Content 696191418 to Machot et al 2011a

Scipediacontent: Created page with " == Abstract == This paper presents a real-time emotion recognition concept of voice streams. A comprehensive solution based on Bayesian Quadratic Discriminate Classifier(QDC..."

2020-10-14T12:59:42Z

Created page with " == Abstract == This paper presents a real-time emotion recognition concept of voice streams. A comprehensive solution based on Bayesian Quadratic Discriminate Classifier(QDC..."

New page

== Abstract ==

This paper presents a real-time emotion recognition concept of voice streams. A comprehensive solution based on Bayesian Quadratic Discriminate Classifier(QDC) is developed. The developed system supports Advanced Driver Assistance Systems (ADAS) to detect the mood of the driver based on the fact that aggressive behavior on road leads to traffic accidents. We use only 12 features to classify between 5 different classes of emotions. We illustrate that the extracted emotion features are highly overlapped and how each emotion class is effecting the recognition ratio. Finally, we show that the Bayesian Quadratic Discriminate Classifier is an appropriate solution for emotion detection systems, where a real-time detection is deeply needed with a low number of features.

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_696191418-beopen684-6941-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf]

← Older revision		Revision as of 12:44, 21 January 2021
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	This paper presents a real-time emotion recognition concept of voice streams. A comprehensive solution based on Bayesian Quadratic Discriminate Classifier(QDC) is developed. The developed system supports Advanced Driver Assistance Systems (ADAS) to detect the mood of the driver based on the fact that aggressive behavior on road leads to traffic accidents. We use only 12 features to classify between 5 different classes of emotions. We illustrate that the extracted emotion features are highly overlapped and how each emotion class is effecting the recognition ratio. Finally, we show that the Bayesian Quadratic Discriminate Classifier is an appropriate solution for emotion detection systems, where a real-time detection is deeply needed with a low number of features.		This paper presents a real-time emotion recognition concept of voice streams. A comprehensive solution based on Bayesian Quadratic Discriminate Classifier(QDC) is developed. The developed system supports Advanced Driver Assistance Systems (ADAS) to detect the mood of the driver based on the fact that aggressive behavior on road leads to traffic accidents. We use only 12 features to classify between 5 different classes of emotions. We illustrate that the extracted emotion features are highly overlapped and how each emotion class is effecting the recognition ratio. Finally, we show that the Bayesian Quadratic Discriminate Classifier is an appropriate solution for emotion detection systems, where a real-time detection is deeply needed with a low number of features.
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−	~~Document type: Part of book or chapter of book~~
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−	~~== Full document ==~~
−	~~<pdf>Media:Draft_Content_696191418-beopen684-6941-document.pdf</pdf>~~


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	* [http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf]		* [http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf]
		+
		+	* [http://link.springer.com/content/pdf/10.1007/978-3-642-24806-1_21 http://link.springer.com/content/pdf/10.1007/978-3-642-24806-1_21],
		+	: [http://dx.doi.org/10.1007/978-3-642-24806-1_21 http://dx.doi.org/10.1007/978-3-642-24806-1_21] under the license http://www.springer.com/tdm
		+
		+	* [http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf http://vi.uni-klu.ac.at/publications/papers/2011A_Novel.pdf],
		+	: [https://link.springer.com/chapter/10.1007%2F978-3-642-24806-1_21 https://link.springer.com/chapter/10.1007%2F978-3-642-24806-1_21],
		+	: [https://dblp.uni-trier.de/db/series/sci/sci391.html#MachotMFSAK12 https://dblp.uni-trier.de/db/series/sci/sci391.html#MachotMFSAK12],
		+	: [https://rd.springer.com/chapter/10.1007/978-3-642-24806-1_21 https://rd.springer.com/chapter/10.1007/978-3-642-24806-1_21],
		+	: [https://academic.microsoft.com/#/detail/126921796 https://academic.microsoft.com/#/detail/126921796]

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