Detecting local semantic concepts in environmental sounds using Markov model based clustering

Detecting the time of occurrence of an acoustic event (for instance, a cheer) embedded in a longer soundtrack is useful and important for applications such as search and retrieval in consumer video archives. We present a Markov-model based clustering algorithm able to identify and segment consistent...

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Bibliographische Detailangaben

Hauptverfasser:	Keansub Lee, Ellis, Daniel P W, Loui, Alexander C
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Acoustic applications Acoustic signal detection Audio Segmentation Cameras Clustering algorithms Data mining Environmental Audio Event detection Markov Models Multiple Instance Learning Video sharing YouTube
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