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Vocal melody extraction using patch-based CNN

Citation Author(s):
Submitted by:
Li Su
Last updated:
17 April 2018 - 8:41am
Document Type:
Poster
Document Year:
2018
Event:
Presenters:
Li Su
Paper Code:
AASP-P7.4
 

A patch-based convolutional neural network (CNN) model presented in this paper for vocal melody extraction in polyphonic music is inspired from object detection in image processing. The input of the model is a novel time-frequency representation which enhances the pitch contours and suppresses the harmonic components of a signal. This succinct data representation and the patch-based CNN model enable an efficient training process with limited labeled data. Experiments on various datasets show excellent speed and competitive accuracy comparing to other deep learning approaches.

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