8 citations · 11 across the 9 of their papers we have counts for
6 papers · 1 filter
MPEcho: A Melody and Phoneme-Aware Generative Framework for Controllable Cover Song Generation
Wei-Jaw Lee, Hsuan-Yu Yeh, Ting-Yi Hu +3
Cover song generation (CSG) should preserve the melodic and linguistic content of a reference song while recreating the remaining musical components. The state-of-the-art model Son…
LargeSHS: A large-scale dataset of music adaptation
Chih-Pin Tan, Hsuan-Kai Kao, Li Su +1
Recent advances in AI-based music generation have focused heavily on text-conditioned models, with less attention given to reference-based generation such as song adaptation. To su…
Segment-Factorized Full-Song Generation on Symbolic Piano Music
Ping-Yi Chen, Chih-Pin Tan, Yi-Hsuan Yang
We propose the Segmented Full-Song Model (SFS) for symbolic full-song generation. The model accepts a user-provided song structure and an optional short seed segment that anchors t…
PiCoGen2: Piano cover generation with transfer learning approach and weakly aligned data
Chih-Pin Tan, Hsin Ai, Yi-Hsin Chang +2
Piano cover generation aims to create a piano cover from a pop song. Existing approaches mainly employ supervised learning and the training demands strongly-aligned and paired song…
PiCoGen: Generate Piano Covers with a Two-stage Approach
Chih-Pin Tan, Shuen-Huei Guan, Yi-Hsuan Yang
Cover song generation stands out as a popular way of music making in the music-creative community. In this study, we introduce Piano Cover Generation (PiCoGen), a two-stage approac…
Music Score Expansion with Variable-Length Infilling
Chih-Pin Tan, Chin-Jui Chang, Alvin W. Y. Su +1
In this paper, we investigate using the variable-length infilling (VLI) model, which is originally proposed to infill missing segments, to "prolong" existing musical segments at mu…