1 citations · 1 across the 6 of their papers we have counts for
6 papers
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…
MIDI-Informed Singing Accompaniment Generation in a Compositional Song Pipeline
Fang-Duo Tsai, Yi-An Lai, Fei-Yueh Chen +4
While end-to-end lyrics-to-song models offer convenience for casual users, professional songwriters require score-to-song systems that allow them to retain authorship over the core…
Training-Efficient Text-to-Music Generation with State-Space Modeling
Wei-Jaw Lee, Fang-Chih Hsieh, Xuanjun Chen +2
Recent advances in text-to-music generation (TTM) have yielded high-quality results, but often at the cost of extensive compute and the use of large proprietary internal data. To i…
Exploring State-Space-Model based Language Model in Music Generation
Wei-Jaw Lee, Fang-Chih Hsieh, Xuanjun Chen +2
The recent surge in State Space Models (SSMs), particularly the emergence of Mamba, has established them as strong alternatives or complementary modules to Transformers across dive…
MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
Fang-Duo Tsai, Shih-Lun Wu, Weijaw Lee +4
We propose MuseControlLite, a lightweight mechanism designed to fine-tune text-to-music generation models for precise conditioning using various time-varying musical attributes and…
Audio Prompt Adapter: Unleashing Music Editing Abilities for Text-to-Music with Lightweight Finetuning
Fang-Duo Tsai, Shih-Lun Wu, Haven Kim +3
Text-to-music models allow users to generate nearly realistic musical audio with textual commands. However, editing music audios remains challenging due to the conflicting desidera…