Zobrazeno 1 - 10
of 82
pro vyhledávání: '"vocal teaching"'
Autor:
Tuva Weideborg Hongve
Publikováno v:
Studia Musicologica Norvegica, Vol 49, Iss 1, Pp 77-91 (2023)
Operasanger Aase Nordmo Løvberg (1923–2013) var en av Norges største operasangere gjennom tidene. Hun var også Norges første professor i sang. I artikkelen beskrives innhold og arbeidsmåter i hennes undervisning basert på en intervjuundersøk
Externí odkaz:
https://doaj.org/article/b2ddef540c664e959e0c1d5cfd008774
Autor:
Shang Xiaoan
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Enhancing the integration of modern information technology with educational practices, particularly in the vocal classroom, is crucial for improving academic quality. This paper presents an optimization method aimed at addressing the limitations of t
Externí odkaz:
https://doaj.org/article/2124e0ae40644cfe83499cffaac2b719
Autor:
Li Ya
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
This paper uses big data analysis to determine user similarity and calculate the bias in selecting nearest neighbors. The temporal factor is introduced to fully reflect the changing status of users’ interest degrees so that the recommendation accur
Externí odkaz:
https://doaj.org/article/07cd938106bc4cc2b6b919a39db63563
Autor:
Du Juan
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, Fourier transforms in big data technology is used to realize the data preprocessing process of vocal signals from analog signals to digital signals and to explore the identification law of various music styles in vocal teaching in coll
Externí odkaz:
https://doaj.org/article/7fd6140cc4c2469ba974ef59a0a74c60
Autor:
Wang Jing
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, we first start from extracting music features and analyze the extraction methods for time-domain, frequency-domain, and cepstrum-domain features of music. Next, the logistic regression model is used to recognize music and deal with two
Externí odkaz:
https://doaj.org/article/970b0096cc6444049dfb838d77aef6ed
Autor:
Shan Jie
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
To be able to better improve musical literacy and artistic aesthetics, this paper presents a study on the application of sentiment analysis for vocal music teaching under natural language processing. Firstly, for the training text that has been label
Externí odkaz:
https://doaj.org/article/34b37edd472e4801b8055acf9c223cfd
Autor:
Fan Fei, Huang Cong
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Due to the diverse development trend of modern media, new media arts and applications are being presented in the field of vocal performance teaching with its many advantages of interactivity, immediacy, sharing, comprehensiveness, versatility, commun
Externí odkaz:
https://doaj.org/article/33074ca00dcd442587e8a72f1a42058c
Autor:
Guan Qingzhen
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Improving timbre recognition and Internet technology have created new avenues for developing vocal teaching models in colleges and universities. In this paper, several people propose a timbre-based Internet vocal teaching model based on the cross-cla
Externí odkaz:
https://doaj.org/article/ef2fcb8f65eb4d16845b9dedd0e6cc0d
Autor:
bilige Gegen
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
The first part of this paper examines the classification of traditional music culture and the method of integrating it with modern vocal teaching. Then, the association rule algorithm was used to establish the calculation model of integrating college
Externí odkaz:
https://doaj.org/article/140e9bd71fac42ecb587b4ebde71e7ab
Autor:
James Poole, Naomi Norton
Publikováno v:
Frontiers in Education, Vol 8 (2023)
This research explores perceptions of dialogic teaching amongst trainee instrumental/vocal teachers enrolled on the MA Music Education: Instrumental and Vocal Teaching programme at the University of York. Thirty students from three different cohorts
Externí odkaz:
https://doaj.org/article/3c47469ba8314bd79e4abbf21eaca005