Extended Pipeline for Content-Based Feature Engineering in Music Genre Recognition

We present a feature engineering pipeline for the construction of musical signal characteristics, to be used for the design of a supervised model for musical genre identification. The key idea is to extend the traditional two-step process of extraction and classification with additive stand-alone ph...

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Veröffentlicht in:	2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) S. 2661 - 2665
Hauptverfasser:	Raissi, Tina, Tibo, Alessandro, Bientinesi, Paolo
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.04.2018
Schlagworte:	autoencoder Feature extraction feature extraction and selection genre classification information gain Mel frequency cepstral coefficient Music Musical signal Pipelines Task analysis Training
ISSN:	2379-190X
Online-Zugang:	Volltext
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