FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models
Text-to-music (TTM) models have recently revolutionized the automatic music generation research field, specifically by being able to generate music that sounds more plausible than all previous state-of-the-art models and by lowering the technical proficiency needed to use them. For these reasons, th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Journal of Imaging |
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| Online Access: | https://www.mdpi.com/2313-433X/11/7/242 |
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| author | Luca Comanducci Paolo Bestagini Stefano Tubaro |
| author_facet | Luca Comanducci Paolo Bestagini Stefano Tubaro |
| author_sort | Luca Comanducci |
| collection | DOAJ |
| description | Text-to-music (TTM) models have recently revolutionized the automatic music generation research field, specifically by being able to generate music that sounds more plausible than all previous state-of-the-art models and by lowering the technical proficiency needed to use them. For these reasons, they have readily started to be adopted for commercial uses and music production practices. This widespread diffusion of TTMs poses several concerns regarding copyright violation and rightful attribution, posing the need of serious consideration of them by the audio forensics community. In this paper, we tackle the problem of detection and attribution of TTM-generated data. We propose a dataset, FakeMusicCaps, that contains several versions of the music-caption pairs dataset MusicCaps regenerated via several state-of-the-art TTM techniques. We evaluate the proposed dataset by performing initial experiments regarding the detection and attribution of TTM-generated audio considering both closed-set and open-set classification. |
| format | Article |
| id | doaj-art-a68183a7f37d4e52a23bcd1fe88a9744 |
| institution | Matheson Library |
| issn | 2313-433X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj-art-a68183a7f37d4e52a23bcd1fe88a97442025-07-25T13:26:33ZengMDPI AGJournal of Imaging2313-433X2025-07-0111724210.3390/jimaging11070242FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music ModelsLuca Comanducci0Paolo Bestagini1Stefano Tubaro2Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milano, ItalyDepartment of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milano, ItalyDepartment of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milano, ItalyText-to-music (TTM) models have recently revolutionized the automatic music generation research field, specifically by being able to generate music that sounds more plausible than all previous state-of-the-art models and by lowering the technical proficiency needed to use them. For these reasons, they have readily started to be adopted for commercial uses and music production practices. This widespread diffusion of TTMs poses several concerns regarding copyright violation and rightful attribution, posing the need of serious consideration of them by the audio forensics community. In this paper, we tackle the problem of detection and attribution of TTM-generated data. We propose a dataset, FakeMusicCaps, that contains several versions of the music-caption pairs dataset MusicCaps regenerated via several state-of-the-art TTM techniques. We evaluate the proposed dataset by performing initial experiments regarding the detection and attribution of TTM-generated audio considering both closed-set and open-set classification.https://www.mdpi.com/2313-433X/11/7/242music generationtext-to-musicaudio forensicsDeepFake |
| spellingShingle | Luca Comanducci Paolo Bestagini Stefano Tubaro FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models Journal of Imaging music generation text-to-music audio forensics DeepFake |
| title | FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models |
| title_full | FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models |
| title_fullStr | FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models |
| title_full_unstemmed | FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models |
| title_short | FakeMusicCaps: A Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models |
| title_sort | fakemusiccaps a dataset for detection and attribution of synthetic music generated via text to music models |
| topic | music generation text-to-music audio forensics DeepFake |
| url | https://www.mdpi.com/2313-433X/11/7/242 |
| work_keys_str_mv | AT lucacomanducci fakemusiccapsadatasetfordetectionandattributionofsyntheticmusicgeneratedviatexttomusicmodels AT paolobestagini fakemusiccapsadatasetfordetectionandattributionofsyntheticmusicgeneratedviatexttomusicmodels AT stefanotubaro fakemusiccapsadatasetfordetectionandattributionofsyntheticmusicgeneratedviatexttomusicmodels |