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In the MIR\u2019s sub-field of main melody extraction, the mainstream methods assume that the main melody is unique. However, the assumption cannot be established, especially for music with multiple main melodies such as symphony or music with many harmonies. Hence, the conventional methods ignore some main melodies in the music. To solve this problem, we propose a deep learning-based Multiple Main Melodies Generator (Multi-MMLG) framework that can automatically predict potential main melodies from a MIDI file. This framework consists of two stages: (1) main melody classification using a proposed MIDIXLNet model and (2) conditional prediction using a modified MuseBERT model. Experiment results suggest that the proposed MIDIXLNet model increases the accuracy of main melody classification from 89.62 to 97.37%. In addition, this model requires fewer parameters (71.8 million) than the previous state-of-art approaches. We also conduct ablation experiments on the Multi-MMLG framework. In the best-case scenario, predicting meaningful multiple main melodies for the music are achieved.<\/jats:p>","DOI":"10.1007\/s00521-023-08924-z","type":"journal-article","created":{"date-parts":[[2023,8,16]],"date-time":"2023-08-16T16:02:22Z","timestamp":1692201742000},"page":"22687-22704","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Multi-mmlg: a novel framework of extracting multiple main melodies from MIDI files"],"prefix":"10.1007","volume":"35","author":[{"given":"Jing","family":"Zhao","sequence":"first","affiliation":[]},{"given":"David","family":"Taniar","sequence":"additional","affiliation":[]},{"given":"Kiki","family":"Adhinugraha","sequence":"additional","affiliation":[]},{"given":"Vishnu Monn","family":"Baskaran","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4893-2291","authenticated-orcid":false,"given":"KokSheik","family":"Wong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,8,16]]},"reference":[{"issue":"6","key":"8924_CR1","first-page":"1669","volume":"24","author":"W-H Tsai","year":"2008","unstructured":"Tsai W-H, Yu H-M, Wang H-M, Horng J-T (2008) Using the similarity of main melodies to identify cover versions of popular songs for music document retrieval. 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