{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/text-based-lstm-networks-for-automatic-music","title":"Text-based LSTM networks for Automatic Music Composition","arxiv_id":"1604.05358","date":"2016-04-18","proceeding":null,"authors":["Keunwoo Choi","George Fazekas","Mark Sandler"],"abstract":"In this paper, we introduce new methods and discuss results of text-based\nLSTM (Long Short-Term Memory) networks for automatic music composition. The\nproposed network is designed to learn relationships within text documents that\nrepresent chord progressions and drum tracks in two case studies. In the\nexperiments, word-RNNs (Recurrent Neural Networks) show good results for both\ncases, while character-based RNNs (char-RNNs) only succeed to learn chord\nprogressions. The proposed system can be used for fully automatic composition\nor as semi-automatic systems that help humans to compose music by controlling a\ndiversity parameter of the model.","url_abs":"http://arxiv.org/abs/1604.05358v1","url_pdf":"http://arxiv.org/pdf/1604.05358v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"text-based-lstm-networks-for-automatic-music","repo_url":"https://github.com/keunwoochoi/LSTMetallica","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"text-based-lstm-networks-for-automatic-music","repo_url":"https://github.com/keunwoochoi/lstm_real_book","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"text-based-lstm-networks-for-automatic-music","repo_url":"https://github.com/AnguloFlorian/jazz-arpeggiator","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"text-based-lstm-networks-for-automatic-music","repo_url":"https://github.com/mattiasu96/TrapGenerator","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}