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» A Bootstrap Method for Training an Accurate Audio Segmenter
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ISMIR
2005
Springer
150views Music» more  ISMIR 2005»
13 years 10 months ago
A Bootstrap Method for Training an Accurate Audio Segmenter
Supervised learning can be used to create good systems for note segmentation in audio data. However, this requires a large set of labeled training examples, and handlabeling is qu...
Ning Hu, Roger B. Dannenberg
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 5 months ago
A framework for classification and segmentation of massive audio data streams
In recent years, the proliferation of VOIP data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voi...
Charu C. Aggarwal
MM
2005
ACM
115views Multimedia» more  MM 2005»
13 years 10 months ago
Accurate repeat finding and object skipping using fingerprints
This paper introduces a novel and very accurate segmentation algorithm. It is very efficient and consumes less than 10% of CPU on a simple desktop PC to segment a stream in real-t...
Cormac Herley
ISMIR
2004
Springer
113views Music» more  ISMIR 2004»
13 years 10 months ago
Audio Features for Noisy Sound Segmentation
Automatic audio classification usually considers sounds as music, speech, silence or noise, but works about the noise class are rare. Audio features are generally specific to sp...
Pierre Hanna, Nicolas Louis, Myriam Desainte-Cathe...
MIR
2003
ACM
178views Multimedia» more  MIR 2003»
13 years 10 months ago
A bootstrapping approach to annotating large image collection
Huge amount of manual efforts are required to annotate large image/video archives with text annotations. Several recent works attempted to automate this task by employing supervis...
HuaMin Feng, Tat-Seng Chua