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• W2040378088 abstract "Audio classification is one of the most important task in content-based analysis and can be implemented in many audio applications, such as indexing and retrieving. This paper addresses the problem of broadcast news audio classification, by support vector machine - binary tree (SVM-BT) architecture, into the five classes: pure speech, speech with music, speech with environment sound, pure music and environment sound. One of the most substantial step in creating such classification architecture is selection of an optimal feature set for each binary SVM classifier. Therefore we implement F-score feature selection algorithm, as an effective search algorithm, within a space of characteristic features that is mostly used for speech/non-speech discrimination." @default.
• W2040378088 created "2016-06-24" @default.
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• W2040378088 date "2012-07-01" @default.
• W2040378088 modified "2023-09-27" @default.
• W2040378088 title "Broadcast news audio classification using SVM binary trees" @default.
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• W2040378088 doi "https://doi.org/10.1109/tsp.2012.6256338" @default.
• W2040378088 hasPublicationYear "2012" @default.
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