Proceedings of the 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017)

Analysis of Features and Singing Skills of Chinese Classical Poetry Songs

Authors
Fangheng Wang
Corresponding Author
Fangheng Wang
Available Online July 2017.
DOI
10.2991/essaeme-17.2017.224How to use a DOI?
Keywords
Chinese classical poetry songs, Artistic characteristics, Singing skills
Abstract

Chinese classical poetry songs are not only an important part of traditional Chinese poetry art, but also the treasure of our national vocal music art. This paper analyzes the characteristics of conception beauty of literature, melody beauty of rhythms, artistic beauty of tunes of Chinese classical poetry songs. This paper also gives the singing skills of Chinese classical poetry songs to provide some references for the relevant researchers.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
July 2017
ISBN
10.2991/essaeme-17.2017.224
ISSN
2352-5398
DOI
10.2991/essaeme-17.2017.224How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Fangheng Wang
PY  - 2017/07
DA  - 2017/07
TI  - Analysis of Features and Singing Skills of Chinese Classical Poetry Songs
BT  - Proceedings of the 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/essaeme-17.2017.224
DO  - 10.2991/essaeme-17.2017.224
ID  - Wang2017/07
ER  -