2000 character limit reached
Retrieval Augmented Generation of Symbolic Music with LLMs
Published 17 Nov 2023 in cs.SD and eess.AS | (2311.10384v2)
Abstract: We explore the use of LLMs for music generation using a retrieval system to select relevant examples. We find promising initial results for music generation in a dialogue with the user, especially considering the ease with which such a system can be implemented. The code is available online.
- T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell et al., “Language models are few-shot learners,” Advances in neural information processing systems, vol. 33, pp. 1877–1901, 2020.
- P. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. Küttler, M. Lewis, W. tau Yih, T. Rocktäschel, S. Riedel, and D. Kiela, “Retrieval-augmented generation for knowledge-intensive nlp tasks,” 2021.
- J. Liu, D. Shen, Y. Zhang, B. Dolan, L. Carin, and W. Chen, “What makes good in-context examples for gpt-3333?” arXiv preprint arXiv:2101.06804, 2021.
- P. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. Küttler, M. Lewis, W.-t. Yih, T. Rocktäschel et al., “Retrieval-augmented generation for knowledge-intensive nlp tasks,” Advances in Neural Information Processing Systems, vol. 33, pp. 9459–9474, 2020.
- J. Zhao and G. Xia, “Accomontage: Accompaniment arrangement via phrase selection and style transfer,” in Proceedings of the 22nd International Society for Music Information Retrieval Conference (ISMIR 2021), 2021, pp. 833–840.
- A. Lv, X. Tan, T. Qin, T.-Y. Liu, and R. Yan, “Re-creation of creations: A new paradigm for lyric-to-melody generation,” 2023.
- S. Bubeck, V. Chandrasekaran, R. Eldan, J. Gehrke, E. Horvitz, E. Kamar, P. Lee, Y. T. Lee, Y. Li, S. Lundberg et al., “Sparks of artificial general intelligence: Early experiments with gpt-4,” arXiv preprint arXiv:2303.12712, 2023.
- OpenAI, “Gpt-4 technical report,” 2023.
- L. Zhang and C. Callison-Burch, “Language models are drummers: Drum composition with natural language pre-training,” arXiv preprint arXiv:2301.01162, 2023.
- P. Jaccard, “The distribution of the flora in the alpine zone.1,” New Phytologist, vol. 11, no. 2, pp. 37–50, 1912. [Online]. Available: https://nph.onlinelibrary.wiley.com/doi/abs/10.1111/j.1469-8137.1912.tb05611.x
- “Introducing chatgpt.” [Online]. Available: https://openai.com/blog/chatgpt
- J. Wei, X. Wang, D. Schuurmans, M. Bosma, F. Xia, E. Chi, Q. V. Le, D. Zhou et al., “Chain-of-thought prompting elicits reasoning in large language models,” Advances in Neural Information Processing Systems, vol. 35, pp. 24 824–24 837, 2022.
- L. Casini and B. L. T. Sturm, “Tradformer: A transformer model of traditional music transcriptions,” in Proc. of the 31st Int. Joint Conf. on Artificial Intelligence, IJCAI-22, 2022.
- B. L. Sturm, J. F. Santos, O. Ben-Tal, and I. Korshunova, “Music transcription modelling and composition using deep learning,” in Proc. Conf. Computer Simulation of Musical Creativity, 2016.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.