基于卷积神经网络(CNN)的传统音乐区域分类

Raymond Luis, N. Rokhman
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引用次数: 0

摘要

印尼传统音乐是印尼文化遗产,经常被现代社会遗忘。许多人不知道传统音乐来自哪个地区。这是一个问题,因为大量的传统音乐失去了它的身份。深度学习技术可以解决这个传统的音乐分类问题。之所以选择传统音乐分类这个主题,是因为以前没有关于这个主题的研究。本研究将使用Youtube的数据,采用梅尔频率倒谱系数(MFCC)特征的提取方法和卷积神经网络(CNN)分类模型,根据来源区域对传统音乐进行分类。有7个省将被用作分类标签,即廖内省、巴布亚省、雅加达特别首都区、日惹特别地区、北苏门答腊省、西爪哇省和南苏拉威西省。本研究产生的分类系统具有良好的分类准确度,值为74.03%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traditional Music Regional Classification using Convolutional Neural Network (CNN)
Traditional Indonesian music is an Indonesian cultural heritage that is often forgotten by modern society. Many people do not know which area the traditional music came from. This is a problem because of the large amount of traditional music that loses its identity. Deep Learning technology can be a solution to this traditional music classification problem. The topic of traditional music classification was chosen because there has been no research using this topic before.This research will classify traditional music based on the area of origin using data from Youtube with the extraction method of the Mel-Frequency Cepstral Coefficients (MFCC) feature and the Convolutional Neural Network (CNN) classification model. There are 7 provinces that will be used as classification labels, namely Riau, Papua, Special Capital District of Jakarta, Special Region of Yogyakarta , North Sumatra, West Java, and South Sulawesi.The classification system produced in this study produced good classification accuracy with a value of 74.03%.
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