Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Journal of Sociology and Ethnology
  4. Vol 4, Issue 11, 2022

On the Core Arguments of Ethnomusicology and Musical Anthropology

Download as PDF

DOI: 10.23977/jsoce.2022.041106 | Downloads: 20 | Views: 499

Author(s)

Qi Wang 1

Affiliation(s)

1 Middle School Attached to Xinjiang Normal University, Urumqi, Xinjiang, 830054, China

Corresponding Author

Qi Wang

ABSTRACT

With the continuous development of China's social economy, national music plays a more and more important role in our life. It is indispensable, indispensable and foundation for the inheritance of human spiritual civilization and traditional culture. In today's society, with the improvement of people's living standards, they also have a higher pursuit of spiritual and cultural aspects. Therefore, music art has become an important way to cause changes in people's inner feelings and aesthetic taste experience. This paper analyzes it from the perspectives of ethnomusicology and anthropology. First, it gives an overview of ethnomusicology, then analyzes its current research situation, and then theoretically expounds and proposes to analyze the music creation style and form characteristics in ethnic minority areas, as well as how to promote better and faster exchanges and cooperation between the people of all ethnic groups in China and promote mutual benefit through localization. After that, this paper adopts the form of questionnaire to investigate the current situation of students' learning of ethnic music. The survey results show that most students learn and learn ethnic music from music classes, the Internet and extramural activities. More than 80% of the respondents are interested in the content of ethnic music knowledge in music textbooks. The frequency of listening to ethnic music is 0.84-0.98, To sum up, it shows that most of the students like China's outstanding and have distinctive local characteristics, educational significance, profound cultural connotation and other characteristics, or a special aesthetic consciousness generated by the combination of national spirit and China's traditional art, which plays a significant role in all aspects of society. At the same time, because of its strong practicality and wide adaptability, So in the whole process, it will greatly improve people's quality of life. 

KEYWORDS

Ethical Musicology, Music Anthropology, Core Arguments, Introduction to Music

CITE THIS PAPER

Qi Wang, On the Core Arguments of Ethnomusicology and Musical Anthropology. Journal of Sociology and Ethnology (2022) Vol. 4: 49-56. DOI: http://dx.doi.org/10.23977/jsoce.2022.041106.

REFERENCES

[1] Hairuddin，N.L., Yusuf，L.M., Othman, M.S. and Nasien, D. (2021) Gender Classification Using A PSO-based Feature Selection and Optimised BPNN in Forensic Anthropology. Int. J. Comput. Aided Eng. Technol. 15(2/3): 232-242.
[2] Antti, Mikael. Rousi. (2021) Ethical Review and Informed Consent Guidelines of High Impact Anthropology, Business, and Education Research Journals. Learn. Publ. 34(3): 339-346.
[3] Charles, M. Djordjevic. (2021) When Clarity and Consistency Conflicts with Empirical Adequacy: Conceptual Engineering, Anthropology, and Evans-Pritchard's Ethnography. Synth. 198(10): 9611-9637.
[4] Nan Du., Chuandong Yu. and Chee-Yong Kim. (2019) Application Research on the Evaluation Index System of Visual Anthropology. J. Multim. Inf. Syst. 6(4): 283-292.
[5] Edmondo, Trentin., Luca, Lusnig. and Fabio,Cavalli. (2018) Parzen Neural Networks: Fundamentals, Properties, and An Application to Forensic Anthropology. Neural Networks 97: 137-151.
[6] Sudipta, Chakrabarty., Ruhul, Islam., Emil, Pricop. and Hiren, Kumar. Deva. Sarma. (2022) An Approach to Discover Similar Musical Patterns. IEEE Access 10: 47322-47339.
[7] Sanket, Rajeev. Sabharwal., Manuel, Varlet., Matthew, Breaden., Gualtiero, Volpe., Antonio, Camurri. and Peter, E. Keller. (2022) Husync - A Model and System for the Measure of Synchronization in Small Groups: A Case Study on Musical Joint Action. IEEE Access 10: 92357-92372.
[8] Karam, Kumar. Sahoo., Ridam,Hazra., Muhammad, FazalIjaz., SeongKi, Kim., Pawan, Kumar. Singh. And Mufti, Mahmud. (2022) MIC_FuzzyNET: Fuzzy Integral Based Ensemble for Automatic Classification of Musical Instruments From Audio Signals. IEEE Access 10: 100797-100811.
[9] Naina,Yadav., Anil, Kumar. Singh. and Sukomal, Pal. (2022) Improved Self-Attentive Musical Instrument Digital Interface Content-Based Music Recommendation System. Comput.Intell. 38(4): 1232-1257.
[10] Lee, Cheatley., Margareta, Ackerman., Alison, Pease. and Wendy, Moncur. (2022) Musical Creativity Support Tools for Bereavement Support. Digit. Creativity 33(1): 1-17.
[11] Davy, Tsz. Kit. Ng., Ellen, H. L. Ng., Samuel, K. W. Chu. (2022) Engaging Students in Creative Music Making with Musical Instrument Application in An Online Flipped Classroom. Educ. Inf. Technol. 27(1): 45-64.
[12] Dawid, Przyczyna., Maria, Szacilowska., Marek, Przybylski., Marcin, Strzelecki. and Konrad, Szacilowski. (2022) Recognition of Musical Dissonance and Consonance in a Simple Neuromorphic Computing System. Int. J. Unconv. Comput. 17(1-2): 81-104.
[13] Nahum, Rangel., Salvador, Godoy-Calderón. and Hiram, Calvo. (2022) Deep Symbolic Processing of Human-Performed Musical Sequences. J. Intell. Fuzzy Syst. 42(5): 4739-4750.
[14] Octave, Etard., Remy, Ben. Messaoud., Gabriel, Gaugain. and Tobias, Reichenbach. (2022) No Evidence of Attentional Modulation of the Neural Response to the Temporal Fine Structure of Continuous Musical Pieces. J. Cogn. Neurosci. 34(3): 411-424.
[15] Lloyd, May., Andrea, R. Halpern., Sean, D. Paulsen. and Michael, A. Casey. (2022) Imagined Musical Scale Relationships Decoded from Auditory Cortex. J. Cogn. Neurosci. 34(8): 1326-1339.
[16] Abraham, George. X., Anitha, Mary. S. and Thomas, George. (2022) Development of An Intelligent Model for Musical Key Estimation Using Machine Learning Techniques. Multim. Tools Appl. 81(14): 19945-19964.
[17] PrithviKantan, Erika. G. and Spaich, Sofia. Dahl. (2022) A Technical Framework for Musical Biofeedback in Stroke Rehabilitation. IEEE Trans. Hum. Mach. Syst. 52(2): 220-231.
[18] Martin, Rohrmeier. (2022) On Creativity, Music's AI Completeness, and Four Challenges for Artificial Musical Creativity. Trans. Int. Soc. Music. Inf. Retr. 5(1): 50-66.

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.