From the 1 of 11 linked papers with an AI index.
11 papers
Genre Bias or Aesthetic Perception? Identifying and Mitigating Shortcut Learning in Music Evaluation
Yizhou Zhang, Wangjin Zhou, Yi Zhao +3
The paper uncovers that music aesthetic scoring models often rely on genre cues as shortcuts, leading to biased evaluations, and introduces a training objective that reweights hard…
LeVo 2: Stable and Melodious Song Generation via Hierarchical Representation Modeling and Progressive Post-Training
Shun Lei, Huaicheng Zhang, Dapeng Wu +8
Full-length song generation must preserve coherence and musicality, render detailed vocal and accompaniment acoustics, and follow lyrics and prompts. Existing language model-based…
SongBench: A Fine-Grained Multi-Aspect Benchmark for Song Quality Assessment
Dapeng Wu, Shun Lei, Wei Tan +5
Recent advancements in Text-to-Song generation have enabled realistic musical content production, yet existing evaluation benchmarks lack the professional granularity to capture mu…
LeVo: High-Quality Song Generation with Multi-Preference Alignment
Shun Lei, Yaoxun Xu, Zhiwei Lin +10
Recent advances in large language models (LLMs) and audio language models have significantly improved music generation, particularly in lyrics-to-song generation. However, existing…
SongBloom: Coherent Song Generation via Interleaved Autoregressive Sketching and Diffusion Refinement
Chenyu Yang, Shuai Wang, Hangting Chen +3
Generating music with coherent structure, harmonious instrumental and vocal elements remains a significant challenge in song generation. Existing language models and diffusion-base…
SongPrep: A Preprocessing Framework and End-to-end Model for Full-song Structure Parsing and Lyrics Transcription
Wei Tan, Shun Lei, Huaicheng Zhang +6
Artificial Intelligence Generated Content (AIGC) is currently a popular research area. Among its various branches, song generation has attracted growing interest. Despite the abund…