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Towards event detection in an audio-based sensor network
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CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
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CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
HMM-Based Acoustic Event Detection with AdaBoost Feature Selection
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Audiovisual laughter detection based on temporal features
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
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MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
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ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
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ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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This paper addresses the problem of highlight sound effects detection in audio stream, which is very useful in fields of video summarization and highlight extraction. Unlike researches on audio segmentation and classification, in this domain, it just locates those highlight sound effects in audio stream. An extensible framework is proposed and in current system three sound effects are considered: laughter, applause and cheer, which are tied up with highlight events in entertainments, sports, meetings and home videos. HMMs are used to model these sound effects and a log-likelihood scores based method is used to make final decision. A sound effect attention model is also proposed to extend general audio attention model for highlight extraction and video summarization. Evaluations on a 2-hours audio database showed very encouraging results.