Proceedings of the 2017 7th International Conference on Social Network, Communication and Education (SNCE 2017)

The Application of Acoustic Analysis in the Study of Yugur Traditional Folk Songs

Authors
Lyu Shiliang, Zhou Luxin
Corresponding Author
Lyu Shiliang
Available Online July 2017.
DOI
10.2991/snce-17.2017.13How to use a DOI?
Keywords
Yugur traditional folk songs; Acoustic analysis; Experimental phonetics
Abstract

Yugur is a unique ethnic minority in Gansu province of China, mainly distributed in the territory of Sunan County in Gansu province. Yugur traditional folk songs recorded in history and culture, is one of the important forms of oral culture. This paper based on the previous research foundation, voice acoustic analysis technology was applied to yugur traditional folk songs research. By summarizing the basic fields and research methods of the study, provide a way for the folk acoustic research and speech research.

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 7th International Conference on Social Network, Communication and Education (SNCE 2017)
Series
Advances in Computer Science Research
Publication Date
July 2017
ISBN
10.2991/snce-17.2017.13
ISSN
2352-538X
DOI
10.2991/snce-17.2017.13How 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  - Lyu Shiliang
AU  - Zhou Luxin
PY  - 2017/07
DA  - 2017/07
TI  - The Application of Acoustic Analysis in the Study of Yugur Traditional Folk Songs
BT  - Proceedings of the 2017 7th International Conference on Social Network, Communication and Education (SNCE 2017)
PB  - Atlantis Press
SP  - 61
EP  - 64
SN  - 2352-538X
UR  - https://doi.org/10.2991/snce-17.2017.13
DO  - 10.2991/snce-17.2017.13
ID  - Shiliang2017/07
ER  -