Uneingeschränkter Zugang

A Study on Automatic Composition for Chinese Wind Piano in the Framework of Autoregressive Language Modeling

   | 11. Dez. 2023

Zitieren

Rhoades, M. (2020). Exploring the nexus of holography and holophony in visual music composition. Leonardo Music Journal, 30(1), 64-70. Search in Google Scholar

Schuiling, F. (2022). Music As Extended Agency: On Notation And Entextualization IN Improvised Music. Music & Letters, 103(2), 322-343. Search in Google Scholar

Vicente, N. E. (2023). Music therapy versus social workers’ stress and fatigue. Journal of Public Health, fdad086. Search in Google Scholar

Robison, T., Edgar, S. N., Eros, J., Councill, K. H., & Williams, B. A. (2020). Inspiring the next generation of music educators: a multiple case study of high school music experiences and career choice. Journal of Research in Music Education(1), 002242942097578. Search in Google Scholar

Snell, A. H., & Stringham, D. A. (2021). Preservice and in-service music educators’ perceptions of functional piano skills. Bulletin of the Council for Research in Music Education, (228), 59-76. Search in Google Scholar

David, O. N. (2022). Piano-playing revisited: what modern players can learn from period instruments. david breitman. Music & Letters(1), 1. Search in Google Scholar

Keil, N., Dahlbom, D. A., Stewart, J., Goodheart, M., & Braasch, J. (2019). Polyphonic pitch perception in rooms using deep learning networks with data rendered in auditory virtual environments. The Journal of the Acoustical Society of America, 145(3), 1784-1784. Search in Google Scholar

Brook, T. (2020). Musicking with music-generation software in virtutes occultae. Leonardo Music Journal, 30, 3-7. Search in Google Scholar

Metcalf, T. (2020). Graphical data sets as compositional structure: sonification of color graphs in rgb for clarinet and piano. Leonardo, 54(1), 1-14. Search in Google Scholar

Coutinho, E., & Schuller, B. (2017). Shared acoustic codes underlie emotional communication in music and speech—Evidence from deep transfer learning. PloS one, 12(6), e0179289. Search in Google Scholar

Zhang, K. (2021). Music style classification algorithm based on music feature extraction and deep neural network. Wireless Communications and Mobile Computing, 2021, 1-7. Search in Google Scholar

Ziemer, T., Kiattipadungkul, P., & Karuchit, T. (2020). Music recommendation based on acoustic features from the recording studio. The Journal of the Acoustical Society of America, 148(4), 2701-2701. Search in Google Scholar

Arthur, P., Khuu, S., & Blom, D. (2021). Visual processing abilities associated with piano music sight-reading expertise. Psychology of Music, 49(4), 1006-1016. Search in Google Scholar

Ann Stolz, B. (2022). The author and the piano student: The transferability of the creative process in practice. International Journal of Music Education, 40(1), 53-65. Search in Google Scholar

Dean, R. T. (2022). The Multi-Tuned Piano: Keyboard Music without a Tuning System. Leonardo, 55(2), 166-169. Search in Google Scholar

Bota, J. V. (2018). The musical creative process involved in the transcription of the composition agnus dei, written by krzysztof penderecki. Musica Hodie, 17(2), 177-188. Search in Google Scholar

Leaman, K. Y. (2022). George Balanchine’s Art of Choreographic Musicality in Tschaikovsky Pas de Deux. Music Theory Spectrum, 44(2), 340-369. Search in Google Scholar

Onyeji, C., & Onyeji, E. (2020). Abigbo music and the ever-evolving present: processing indigenous music as an indicator of communal experience among the Mbaise, Igbo. Journal of the Musical Arts in Africa, 17(1), 81-99. Search in Google Scholar

Holzapfel, A., Benetos, E., Killick, A., & Widdess, R. (2022). Humanities and engineering perspectives on music transcription. Digital Scholarship in the Humanities, 37(3), 747-764. Search in Google Scholar

Wulff, P., Mientus, L., Nowak, A., & Borowski, A. (2023). Correction to: Utilizing a Pretrained Language Model (BERT) to Classify Preservice Physics Teachers’ Written Refections. International Journal of Artificial Intelligence in Education, 1-1. Search in Google Scholar

Loc, C. V., Viet, T. X., Viet, T. H., Thao, L. H., & Viet, N. H. (2023). Pre-Trained Language Model-Based Deep Learning for Sentiment Classification of Vietnamese Feedback. International Journal of Computational Intelligence and Applications, 2350016. Search in Google Scholar

Suan, T., Cai, R., Cai, Z., Zu, B., & Gong, B. (2021). A language model for amdo tibetan speech recognition. MATEC Web of Conferences, 336(3), 06016. Search in Google Scholar

eISSN:
2444-8656
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
Volume Open
Fachgebiete der Zeitschrift:
Biologie, andere, Mathematik, Angewandte Mathematik, Allgemeines, Physik