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eess.AS2026

The ICASSP 2026 Automatic Song Aesthetics Evaluation Challenge

Guobin Ma, Yuxuan Xia, Jixun Yao +5

This paper summarizes the ICASSP 2026 Automatic Song Aesthetics Evaluation (ASAE) Challenge, which focuses on predicting the subjective aesthetic scores of AI-generated songs. The…

eess.AS2025

MeanVC: Lightweight and Streaming Zero-Shot Voice Conversion via Mean Flows

Guobin Ma, Jixun Yao, Ziqian Ning +4

Zero-shot voice conversion (VC) aims to transfer timbre from a source speaker to any unseen target speaker while preserving linguistic content. Growing application scenarios demand…

eess.AS2025

DiffRhythm+: Controllable and Flexible Full-Length Song Generation with Preference Optimization

Huakang Chen, Yuepeng Jiang, Guobin Ma +7

Songs, as a central form of musical art, exemplify the richness of human intelligence and creativity. While recent advances in generative modeling have enabled notable progress in…

eess.AS2025

SongEval: A Benchmark Dataset for Song Aesthetics Evaluation

Jixun Yao, Guobin Ma, Huixin Xue +9

Aesthetics serve as an implicit and important criterion in song generation tasks that reflect human perception beyond objective metrics. However, evaluating the aesthetics of gener…

eess.AS2025

DiffRhythm: Blazingly Fast and Embarrassingly Simple End-to-End Full-Length Song Generation with Latent Diffusion

Ziqian Ning, Huakang Chen, Yuepeng Jiang +5

Recent advancements in music generation have garnered significant attention, yet existing approaches face critical limitations. Some current generative models can only synthesize e…

eess.AS2025

LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech Enhancement

Boyi Kang, Xinfa Zhu, Zihan Zhang +10

Recent advancements in language models (LMs) have demonstrated strong capabilities in semantic understanding and contextual modeling, which have flourished in generative speech enh…