Pretrained audio models show large performance gaps between standard MIR tasks and music recommendation in both hot and cold-start settings.
arXiv preprint arXiv:2107.05677 , year =
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Compares from-scratch spectrogram models and frozen pretrained music embeddings on cross-performance jazz standard recognition using supervised probing and nearest-neighbor retrieval on a Jazz Trio Database subset.
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Adopting State-of-the-Art Pretrained Audio Representations for Music Recommender Systems
Pretrained audio models show large performance gaps between standard MIR tasks and music recommendation in both hot and cold-start settings.
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Evaluating Pretrained Music Embeddings for Cross-Performance Jazz Standard Recognition
Compares from-scratch spectrogram models and frozen pretrained music embeddings on cross-performance jazz standard recognition using supervised probing and nearest-neighbor retrieval on a Jazz Trio Database subset.