Harmonic Classification with Enhancing Music Using Deep Learning Techniques

Automatic extraction of features from harmonic information of music audio is considered in this paper. Automatically obtaining of relevant information is necessary not just for analysis but also for the commercial issue such as music program of tutoring and generating of lead sheet. Two aspects of h...

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Main Authors: Wen Tang, Linlin Gu
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2021/5590996
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author Wen Tang
Linlin Gu
author_facet Wen Tang
Linlin Gu
author_sort Wen Tang
collection DOAJ
description Automatic extraction of features from harmonic information of music audio is considered in this paper. Automatically obtaining of relevant information is necessary not just for analysis but also for the commercial issue such as music program of tutoring and generating of lead sheet. Two aspects of harmony are considered, chord and global key, facing the issue of the extraction problem by the algorithm of machine learning. Contribution here is to recognize chords in the music by the feature extraction method (voiced models) that performd better than manually one. The modelling carried out chord sequence, getting from frame-by-frame basis, which is known in recognition of the chord system. Technique of machine learning such the convolutional neural network (CNN) will systematically extract the chord sequence to achieve the superiority context model. Then, traditional classification is used to create the key classifier which is better than others or manually one. Datasets used to evaluate the proposed model show good achievement results compared with existing one.
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spelling doaj-art-9ba106c1c5a54b199b6fbfd7e8ae98452025-02-03T01:27:07ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55909965590996Harmonic Classification with Enhancing Music Using Deep Learning TechniquesWen Tang0Linlin Gu1School of Art and Design, Nanchang University, Nanchang, ChinaSchool of Art and Design, Nanchang University, Nanchang, ChinaAutomatic extraction of features from harmonic information of music audio is considered in this paper. Automatically obtaining of relevant information is necessary not just for analysis but also for the commercial issue such as music program of tutoring and generating of lead sheet. Two aspects of harmony are considered, chord and global key, facing the issue of the extraction problem by the algorithm of machine learning. Contribution here is to recognize chords in the music by the feature extraction method (voiced models) that performd better than manually one. The modelling carried out chord sequence, getting from frame-by-frame basis, which is known in recognition of the chord system. Technique of machine learning such the convolutional neural network (CNN) will systematically extract the chord sequence to achieve the superiority context model. Then, traditional classification is used to create the key classifier which is better than others or manually one. Datasets used to evaluate the proposed model show good achievement results compared with existing one.http://dx.doi.org/10.1155/2021/5590996
spellingShingle Wen Tang
Linlin Gu
Harmonic Classification with Enhancing Music Using Deep Learning Techniques
Complexity
title Harmonic Classification with Enhancing Music Using Deep Learning Techniques
title_full Harmonic Classification with Enhancing Music Using Deep Learning Techniques
title_fullStr Harmonic Classification with Enhancing Music Using Deep Learning Techniques
title_full_unstemmed Harmonic Classification with Enhancing Music Using Deep Learning Techniques
title_short Harmonic Classification with Enhancing Music Using Deep Learning Techniques
title_sort harmonic classification with enhancing music using deep learning techniques
url http://dx.doi.org/10.1155/2021/5590996
work_keys_str_mv AT wentang harmonicclassificationwithenhancingmusicusingdeeplearningtechniques
AT linlingu harmonicclassificationwithenhancingmusicusingdeeplearningtechniques