Comparative Symbolic Analysis of the Ethno-Fusion Genre: Insights and Perspectives

1 Ali C. Gedik, B. B. (2010). Pitch-frequency histogram-based music information retrieval for Turkish music. Elsevier, 1049-1063. doi:10.1016/j.sigpro.2009.06.017 Search in Google Scholar

2 Anand, V. V. (2020). Music Genre Clasification with Deep Learning. SCOPUS, 1-6. Search in Google Scholar

3 Briot, J. (2021). From artificial neural networks to deep learning for music generation: history, concepts and trends. Neural Comput & Applic, Springer, 31-65. doi:10.1007/s00521-020-05399-0 Search in Google Scholar

4 Chen, Y.-H. H.-Y.-H.-H. (2020). Automatic Composition of Guitar Tabs by Transformers and Groove Modeling. Accepted at Proc. Int. Society for Music Information Retrieval Conf. 2020, 1-5. Search in Google Scholar

5 Chris Donahue, H. H. (2019). LakhNES: Improving multi-instrumental music generation with cross-domain pre-training. arXiv:1907.04868 [cs.SD], 1-8. Search in Google Scholar

6 Colton, B. B. (2021). A QUALITY-DIVERSITY-BASED EVALUATION STRATEGY FOR SYMBOLIC MUSIC GENERATION. ML Evaluation Standards Workshop at ICLR, 1-6. Search in Google Scholar

7 Curtis Hawthorne, A. S.-Z. (2019). Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset. In International Conference on Learning Representations, 2019., (p. Version 2.0). Search in Google Scholar

8 DuBreuil, A. (2020). Music Composition with Magenta. Birmingham: Packt. Search in Google Scholar

9 G′omez, N. K. (2015). Automatic Transcription of Flamenco Singing from. arXiv:1510.04039v1 [cs.SD] IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, 1-16. Search in Google Scholar

10 Gatti, G. O. (2017). Automatic generation of lyrics parodies. In Proc. ACM Multimedia, 485-491. Search in Google Scholar

11 Hawthorne, I. S. (2021). Sequence-to-Sequence Piano Transcription with Transformers. Sound (cs.SD); Machine Learning (cs:LG); Audio and Speech Procesing (eess.AS), 35-40. Search in Google Scholar

12 I. Barbancho, L. J. (2012). Inharmonicity-Based Method for the Automatic Generation of Guitar Tablature. IEEE Transactions on Audio, Speech, and Language Processing, 1857-1868. Search in Google Scholar

13 Kentaro Shibataa, E. N. (2021). Non-Local Musical Statistics as Guides for Audio-to-Score Piano Transcription. arXiv:2008.12710v3 [cs.SD], 1-16. Search in Google Scholar

14 Kong, Q. L. (2021). High-resolution piano transcription with pedals by regressing onsets and offsets times. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 3707–3717. Search in Google Scholar

15 Martineau, J. (2008). The Elements of Music: Melody, Rhythm and Harmony. 1-6. Search in Google Scholar

16 N. Rosmawarni, T. T. (2023). "Handcrafted Feature From Classification Mood Music Indonesia With Machine Learning BERT and Transformer. 2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS), 526-531. doi:10.1109/ICIMCIS60089.2023.10349006. Search in Google Scholar

17 N. Rosmawarni, T. T. (2023). Hyperparameter Tuning On Machine Learning Transformers For Mood Classification In Indonesian Music. 2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS), 639-643. doi:10.1109/ICIMCIS60089.2023.10349008. Search in Google Scholar

18 Nakamura, E. Y. (2017). Performance error detection and post-processing for fast and accurate symbolic music alignment. In International Society for Music Information Retrieval (ISMIR), 347–353. Search in Google Scholar

19 Oore, I. S. (2018). This time with feeling: Learning expressive musical performance. Neural Computing and Aplications, 50-62. Search in Google Scholar

20 Peterson, G. H. (2017). Integrating Computer Science into Music Education. Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 459-464. Search in Google Scholar

21 Qiu, Z. Y. (2023). Generated Therapeutic Music Based on the ISO Principle. Communications in Computer and Information Science, Springer, 32-45. Search in Google Scholar

22 Qiuqiang Kong, B. L. (2022). GiantMIDI-Piano: A large-scale MIDI Dataset for Classical Piano Music. symarXiv:2010.07061v3, 1-11. Search in Google Scholar

23 Sarmento, P. K. (2023). GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers. (eds) Artificial Intelligence in Music, Sound, Art and Design, Springer, 260-275. Search in Google Scholar

24 Shih-Lun Wu, Y.-H. Y. (2022). MuseMorphose: Full-Song and Fine-Grained Piano Music Style Transfer with One Transformer VAE. arXiv:2105.04090 [cs.SD], 1-8. Search in Google Scholar

25 Silla, A. L. (2017). Music education meets computer science and engineering education. 2016 IEE Frontiers in Education Conference, 1-7. Search in Google Scholar

26 Sreetama Mukherjee, M. M. (2022). ComposeInStyle: Music composition with and without Style Transfer. ELSEVIER. Search in Google Scholar

27 Xianchao Wu, C. W. (2020). Transformer-XL Based Music Generation with Multiple Sequences of Time-valued Notes. Multimedia (cs.MM); Audio and Speech Processing (eess.AS), 1-9. Search in Google Scholar

28 Yu-Hua Chen, Y.-H. H.-Y.-H. (2020). Automatic Composition of Guitar Tabs by Transformers and Groove Modeling. arXiv:2008.01431 [cs.SD], 1-8. Search in Google Scholar