The MAHNOB Laughter database
نویسندگان
چکیده
Article history: Received 25 October 2011 Received in revised form 2 August 2012 Accepted 23 August 2012 Available online xxxx
منابع مشابه
Combining acoustic and visual features to detect laughter in adults' speech
Laughter can not only convey the affective state of the speaker but also be perceived differently based on the context in which it is used. In this paper, we focus on detecting laughter in adults’ speech using the MAHNOB laughter database. The paper explores the use of novel long-term acoustic features to capture the periodic nature of laughter and the use of computer vision-based smile feature...
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Prediction-based fusion is a recently proposed audiovisual fusion approach which outperforms feature-level fusion on laughter-vs-speech discrimination. One set of predictive models is trained per class which learns the audio-to-visual and visual-to-audio feature mapping together with the time evolution of audio and visual features. Classification of a new input is performed via prediction. All ...
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Emotion recognition from physiological signals attracted the attention of researchers from different disciplines, such as affective computing, cognitive science and psychology. This paper aims to classify emotional statements using peripheral physiological signals based on arousal-valence evaluation. These signals are the Electrocardiogram, Respiration Volume, Skin Temperature and Galvanic Skin...
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In this paper, we present the detailed phonetic annotation of the publicly available AVLaughterCycle database, which can readily be used for automatic laughter processing (analysis, classification, browsing, synthesis, etc.). The phonetic annotation is used here to analyze the database, as a first step. Unsurprisingly, we find that h-like phones and central vowels are the most frequent sounds i...
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عنوان ژورنال:
- Image Vision Comput.
دوره 31 شماره
صفحات -
تاریخ انتشار 2013