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DNN in the AcousticBrainz Genre Task 2017

Nicolas Dauban
2017 MediaEval Benchmarking Initiative for Multimedia Evaluation  
This paper presents a method of genre classification using deep neural networks for the AcousticBrainz genre classification task of MediaEval 2017.  ...  INTRODUCTION The AcousticBrainz Genre Task 2017 is a music genre recognition (MGR) task organised by MediaEval [1] where participants had to make predictions on genre and subgenres, based on audio features  ...  -AcousticBrainz-Genre-Task/results/  ... 
dblp:conf/mediaeval/Dauban17 fatcat:wb7crl6lsjaczgcmsecfekt7dm

Single and Multi Column Neural Networks for Content-based Music Genre Recognition

Chang Wook Kim, Jaehun Kim, Kwangsub Kim, Minz Won
2017 MediaEval Benchmarking Initiative for Multimedia Evaluation  
This working note reports approaches of team KART to Media-Eval2017 AcousticBrainz Genre Task and their results.  ...  To solve the problem, we mainly considered the sparsity and noise of data, network design for the multi-label classification, and implementation of successful Deep Neural Network (DNN) models.  ...  The MediaEval2017 AcousticBrainz Genre Task aims to predict the genre and subgenre of unlabeled music recordings from four different datasets which consist of four different genre/subgenre taxonomies  ... 
dblp:conf/mediaeval/KimKKW17 fatcat:lm5z6ylcprcz5j72vow3sd5w2e

Machine learning for music genre: multifaceted review and experimentation with audioset

Jaime Ramírez, M. Julia Flores
2019 Journal of Intelligent Information Systems  
Although research has been prolific in terms of number of published works, the topic still suffers from a problem in its foundations: there is no clear and formal definition of what genre is.  ...  In its first part, this paper offers a survey trying to cover the many different aspects of the matter.  ...  Acknowledgements This work has been partially funded by FEDER funds and the Spanish Government (MICINN) through projects SBPLY/17/180501/000493 and TIN2016-77902-C3-1-P.  ... 
doi:10.1007/s10844-019-00582-9 fatcat:ajs4sfhtufd6lijtkf4icjhtii

Automatic Assessment Of Singing Voice Pronunciation: A Case Study With Jingju Music

Rong Gong, Xavier Serra
2018 Zenodo  
Automatic singing voice assessment, as an important task in Music Information Research (MIR), aims to extract musically meaningful information and measure the quality of learners' singing voice.  ...  Online learning has altered music education remarkable in the last decade.  ...  Corpora and datasets Access to the corpora and datasets will be through the Zenodo.org and MusicBrainz.org Research corpus  ... 
doi:10.5281/zenodo.1490343 fatcat:f3mrhstkdff6ppmdadeasfuo7m

A Comparison of Audio Preprocessing Methods for Music Autotagging using CNN-architectures

Maximilian Damböck, Peter Knees
2022
CNNs have become famous for their outstanding results in various computer vision tasks in the last decade.  ...  Their ability to capture large receptive fields while keeping the resource consumption low can be interesting for the genre- and mood classification.  ...  command recognition (Speech Commands Dataset) and acoustic scene tagging (DCASE 2017 Task 4).  ... 
doi:10.34726/hss.2022.89400 fatcat:zaal6nl4vbbvtherp7zgd6blgu