7 papers · 1 filter
Discrete vs. Continuous: A Comprehensive Study of Unified Audio Understanding in LALMs
Jing Peng, Zichao Nie, Zhisheng Zhang +2
Large Audio Language Models (LALMs) utilize either continuous features or discrete tokens, yet the optimal representation paradigm for general audio understanding remains debated.…
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…
Self-Guidance: Enhancing Neural Codecs via Decoder Manifold Alignment
Xiang Li, Yixuan Zhou, Jingran Xie +2
Neural speech codecs based on Vector-Quantized VAEs (VQ-VAEs) are core audio tokenizers for speech LLMs, yet their reconstruction fidelity is bottlenecked by quantization error. Mo…
WAKE: Watermarking Audio with Key Enrichment
Yaoxun Xu, Jianwei Yu, Hangting Chen +5
As deep learning advances in audio generation, challenges in audio security and copyright protection highlight the need for robust audio watermarking. Recent neural network-based m…
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…
VoiceMark: Zero-Shot Voice Cloning-Resistant Watermarking Approach Leveraging Speaker-Specific Latents
Haiyun Li, Zhiyong Wu, Xiaofeng Xie +3
Voice cloning (VC)-resistant watermarking is an emerging technique for tracing and preventing unauthorized cloning. Existing methods effectively trace traditional VC models by trai…