論文

査読有り
2019年

深層学習による琉球古典音楽のリアルタイム推論

電気学会論文誌C(電子・情報・システム部門誌)
  • 長濱 嗣志
  • ,
  • 上原 一朗
  • ,
  • 宮城 桂
  • ,
  • 山田 親稔
  • ,
  • 市川 周一

139
9
開始ページ
1001
終了ページ
1007
記述言語
日本語
掲載種別
DOI
10.1541/ieejeiss.139.1001
出版者・発行元
一般社団法人 電気学会

<p>The classical music "uta-sanshin" has been sung since the Ryukyu Kingdom period, and its skills commonly depend on folklore method by bush telegraph. Accordingly, there exist much sensibilities and esoteric expressions of the uta-sanshin expert in passing down the skill. Also, the decrease in number of successors accompanying aging and the difficulty in understanding the musical score are hindering the inheritance and the reconstruction of the music. In this paper, we apply the deep learning to Ryukyuan classical music and develop a system that identifies vocalism by real-time processing. The results of the evaluation, compared with the conventional method, show that the execution time is reduced to 98%, and the identification accuracy is improved by 6%.</p>

リンク情報
DOI
https://doi.org/10.1541/ieejeiss.139.1001
CiNii Articles
http://ci.nii.ac.jp/naid/130007700096
CiNii Books
http://ci.nii.ac.jp/ncid/AN10065950
URL
http://id.ndl.go.jp/bib/029972198
ID情報
  • DOI : 10.1541/ieejeiss.139.1001
  • ISSN : 0385-4221
  • CiNii Articles ID : 130007700096
  • CiNii Books ID : AN10065950

エクスポート
BibTeX RIS