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Laughter Detection for an Assisting Tool of Group Conversation

Myagmarbayar Nergui and Mihoko Otake
Mechanical Engineering Department, Graduate School of Engineering, Chiba University, Yayoi-cho 1-33, Inage-ku, Chiba-shi, Japan
Abstract—In super aged society, population with age related disease such as dementia increases, which is disorder of brain functions. Interactive group conversation or group activities play an important role of activating brain functions. In order to make interactive group conversation among older people for preventing or inhibiting the progress of mild cognitive decline and dementia, our research aims to develop a system assisting group conversation, which is capable of detecting laughter and emotions, and recognizing speech contents of the participants. This study is a part of the developing system to recognize laughter from acoustic signals of group conversation. Mel frequency Cepstral Coefficients (MFCCs) are calculated and vector quantized from the acoustic signals. Minimum distance classifier is applied for recognition of laughing and non-laughing states. Experimental results show very good performance. F-score and accuracy rate are 88% and 98%, respectively.

Index Terms—laughter detection, group conversation, dementia, mel frequency cepstral coefficents (MFCC)

Cite: Myagmarbayar Nergui and Mihoko Otake, "Laughter Detection for an Assisting Tool of Group Conversation," International Journal of Signal Processing Systems, Vol. 1, No. 2, pp. 212-217, December 2013. doi: 10.12720/ijsps.1.2.212-217

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