We introduce JamendoMaxCaps, a large-scale music-caption dataset featuring over 362,000 freely licensed instrumental tracks from the renowned Jamendo platform. The dataset includes captions generated by a state-of-the-art captioning model, enhanced with imputed metadata. We also introduce a retrieval system that leverages both musical features and metadata to identify similar songs, which are then used to fill in missing metadata using a local large language model (LLLM). This approach allows us to provide a more comprehensive and informative dataset for researchers working on music-language understanding tasks. We validate this approach quantitatively with five different measurements. By making the JamendoMaxCaps dataset publicly available, we provide a high-quality resource to advance research in music-language understanding tasks such as music retrieval, multimodal representation learning, and generative music models.
JamendoMaxCaps: A Large Scale Music-caption Dataset with Imputed Metadata
JamendoMaxCaps is a large-scale music-caption dataset with over 200,000 tracks, featuring captions from a state-of-the-art model and imputed metadata, used to enhance music-language understanding research.
- Year
- 2025
- Venue
- arXiv 2025
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- 4
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2502.07461v2ARXIV-DEFAULT
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