Spatial audio large language models (LLMs) enable embodied agents, wearable assistants, and immersive systems to recognize sound events, localize sources, and reason about their spatial relationships. However, existing spatial audio LLMs often rely on early fusion of acoustic and spatial features and source-agnostic to...
Zheng-Ding Luo, Jin-Yang Wu, Hao-Zhe Ma et al.· 0 citations
A hierarchical clustering algorithm is applied to analyse whether prepared speaker embeddings naturally form clusters with hierarchical relationships, and a new method is proposed, termed Hierarchical Cluster-Class Matching (HCCM), to identify which hierarchical clusters best match individual semantic classes like male...
Yanze Xu, Wen-Wu Wang, Mark D. Plumbley· 0 citations
This work proposes FlowSep2, a text-conditioned flow-matching generative model for LASS, which learns to generate the target source representation from Gaussian noise in a latent space, conditioned on both the mixture representation and the text query.
Yiitan Yuan, Xu-Bo Liu, Haohe Liu et al.· 0 citations
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