Non-Linguistic Vocal Event Detection Using Online Random

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Abstrakt

Accurate detection of non-linguistic vocal events in social signals can have a great impact on the applicability of speech enabled interactive systems. In this paper, we investigate the use of random forest for vocal event detection. Random forest technique has been successfully employed in many areas such as object detection, face recognition, and audio event detection. This paper proposes to use online random forest technique for detecting laughter and filler and for analyzing the importance of various features for non-linguistic vocal event classification through permutation. The results show that according to the Area Under Curve measure the online random forest achieved 88.1% compared to 82.9% obtained by the baseline support vector machines for laughter classification and 86.8% to 83.6% for filler classification.
OriginalsprogEngelsk
TitelInformation and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 37th International Convention on
ForlagIEEE Press
Publikationsdato2014
Sider1326 - 1330
ISBN (Trykt)978-953-233-081-6
DOI
StatusUdgivet - 2014
Begivenhed2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics - Opatija, Kroatien
Varighed: 26 maj 201430 maj 2014
Konferencens nummer: 33202

Konference

Konference2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics
Nummer33202
LandKroatien
ByOpatija
Periode26/05/201430/05/2014

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