collaborators

6 papers

eess.AS2026

PhASE-Flow: Phonetic-Conditioned Acoustic Flow Matching in SSL Representation Domain for Speech Enhancement

Jun Gao, Xiaobin Rong, Yu Sun +2

Flow matching (FM) enables high-fidelity generation, while self-supervised learning (SSL) speech models provide hierarchical representations spanning acoustic and phonetic levels.…

eess.AS2026

HALO: Half-Frame-Rate Adaptive Learnable Operator for Lightweight STFT-Based Speech Enhancement

Jiadong Zhao, Dahan Wang, Yu Sun +5

STFT-based speech enhancement typically adopts overlapping analysis frames. While overlap is essential for stable STFT processing, it makes adjacent frames highly correlated, causi…

cs.CV2026

Native Audio-Visual Alignment for Generation

Longbin Ji, Guan Wang, Xuan Wei +6

Joint audio-video generation aims to synthesize temporally synchronized and semantically coherent visual-acoustic content. However, existing open-source methods mainly rely on eith…

cs.SD2026

Eureka-Audio: Triggering Audio Intelligence in Compact Language Models

Dan Zhang, Yishu Lei, Jing Hu +10

We present Eureka-Audio, a compact yet high-performance audio language model that achieves competitive performance against models that are 4 to 18 times larger across a broad range…

cs.SD2026

CORD: Bridging the Audio-Text Reasoning Gap via Weighted On-policy Cross-modal Distillation

Jing Hu, Danxiang Zhu, Xianlong Luo +9

Large Audio Language Models (LALMs) have garnered significant research interest. Despite being built upon text-based large language models (LLMs), LALMs frequently exhibit a degrad…

cs.SD2026

MoE Adapter for Large Audio Language Models: Sparsity, Disentanglement, and Gradient-Conflict-Free

Yishu Lei, Shuwei He, Jing Hu +9

Extending the input modality of Large Language Models~(LLMs) to the audio domain is essential for achieving comprehensive multimodal perception. However, it is well-known that acou…