Convolutional Neural Networks and Transfer Learning Applied to Automatic Composition of Descriptive Music

被引：0

作者：

Martin-Gomez, Lucia ^{[1
]}

Perez-Marcos, Javier ^{[1
]}

Navarro-Caceres, Maria ^{[1
]}

Rodriguez-Gonzalez, Sara ^{[1
]}

机构：

[1] Univ Salamanca, BISITE Digital Innovat Hub, Edificio Multiusos I D I, Salamanca 37007, Spain

来源：

DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE | 2019年 / 801卷

关键词：

Descriptive music; Automatic composition; Image; Video; Transfer learning; Convolutional neural networks;

D O I：

10.1007/978-3-319-99608-0_31

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Visual and musical arts has been strongly interconnected throughout history. The aim of this work is to compose music on the basis of the visual characteristics of a video. For this purpose, descriptive music is used as a link between image and sound and a video fragment of film Fantasia is deeply analyzed. Specially, convolutional neural networks in combination with transfer learning are applied in the process of extracting image descriptors. In order to establish a relationship between the visual and musical information, Naive Bayes, Support Vector Machine and Random Forest classifiers are applied. The obtained model is subsequently employed to compose descriptive music from a new video. The results of this proposal are compared with those of an antecedent work in order to evaluate the performance of the classifiers and the quality of the descriptive musical composition.

引用

页码：275 / 282

页数：8

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