We present Musda: Music data augmentation techniques for boosting performance on music generation tasks.
Musda consists six simple but powerful operations: random addition, random shift, random remove, duration float, velocity float and transposition.
On music generation tasks, we show that Musda improves performance and demonstrates particularly strong results for small music datasets in both qualitative and quantitative evaluation.