5 papers
CLASVS: Continuous-Latent Autoregression for Melody-Preserving Lyric Editing in Singing Voice Synthesis
Yizhong Geng, Tian-Hao Zhang, Chunfeng Wang +7
Reference-conditioned melody-preserving lyric editing replaces words while retaining a performance's timing, singer identity, and naturalness. Continuous-latent autoregression avoi…
MeloCodec: Harnessing Melodic Priors for High-Fidelity Singing Voice Representation
Yizhong Geng, Wenxin Fu, Kecan Mao +7
Neural audio codecs serve as fundamental tokenizers for LLM-based audio generation. While semantic priors are widely exploited to enhance linguistic intelligibility, the integratio…
Multi-Loss Learning for Speech Emotion Recognition with Energy-Adaptive Mixup and Frame-Level Attention
Cong Wang, Yizhong Geng, Yuhua Wen +7
Speech emotion recognition (SER) is an important technology in human-computer interaction. However, achieving high performance is challenging due to emotional complexity and scarce…
HQ-SVC: Towards High-Quality Zero-Shot Singing Voice Conversion in Low-Resource Scenarios
Bingsong Bai, Yizhong Geng, Fengping Wang +4
Zero-shot singing voice conversion (SVC) transforms a source singer's timbre to an unseen target speaker's voice while preserving melodic content without fine-tuning. Existing meth…
Mel-Refine: A Plug-and-Play Approach to Refine Mel-Spectrogram in Audio Generation
Hongming Guo, Ruibo Fu, Yizhong Geng +9
Text-to-audio (TTA) model is capable of generating diverse audio from textual prompts. However, most mainstream TTA models, which predominantly rely on Mel-spectrograms, still face…