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This paper introduces TunesFormer, an efficient Transformer-baseddual-decoder model specifically designed for the generation of melodies thatadhere to user-defined musical forms. Trained on 214,122 Irish tunes,TunesFormer utilizes techniques including bar patching and control codes. Barpatching reduces sequence length and generation time, while control codes guideTunesFormer in producing melodies that conform to desired musical forms. Ourevaluation demonstrates TunesFormer's superior efficiency, being 3.22 timesfaster than GPT-2 and 1.79 times faster than a model with linear complexity ofequal scale while offering comparable performance in controllability and othermetrics. TunesFormer provides a novel tool for musicians, composers, and musicenthusiasts alike to explore the vast landscape of Irish music. Our model andcode are available at https://github.com/sander-wood/tunesformer.

TunesFormer: Forming Irish Tunes with Control Codes by Bar Patching