MusicQA
Introduced by Liu et al. in Music Understanding LLaMA: Advancing Text-to-Music Generation with Question Answering and Captioning
We propose the MusicQA dataset to train Music-enabled question-answering models and is used for training and evaluating our MU-LLaMA model. This dataset is generated using the MusicCaps and MagnaTagATune datasets. We utilize the descriptions/tags from existing datasets to prompt the MPT-7B Chat model to generate question-answer pairs through inference, reasoning, and paraphrasing. The dataset contains 12,542 music files for training making up 76.15 hours of music with 112,878 question-answer pairs.
Benchmarks
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MusicQA
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MU-LLaMA
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Papers
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