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2010
IEEE

Homogeneous segmentation and classifier ensemble for audio tag annotation and retrieval

12 years 1 months ago
Homogeneous segmentation and classifier ensemble for audio tag annotation and retrieval
Audio tags describe different types of musical information such as genre, mood, and instrument. This paper aims to automatically annotate audio clips with tags and retrieve relevant clips from a music database by tags. Given an audio clip, we divide it into several homogeneous segments by using an audio novelty curve, and then extract audio features from each segment with respect to various musical information, such as dynamics, rhythm, timbre, pitch, and tonality. The features in frame-based feature vector sequence format are further represented by their mean and standard deviation such that they can be combined with other segment-based features to form a fixed-dimensional feature vector for a segment. We train an ensemble classifier, which consists of SVM and AdaBoost classifiers, for each tag. For the audio annotation task, the individual classifier outputs are transformed into calibrated probability scores such that probability ensemble can be employed. For the audio retrieval tas...
Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ICMCS
Authors Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang
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