DeFT-Mamba: Universal Multichannel Sound Separation and Polyphonic Audio Classification
This paper presents a framework for universal sound separation and polyphonic audio classification, addressing the challenges of separating and classifying individual sound sources in a multichannel mixture. The proposed framework, DeFT-Mamba, utilizes the dense frequency-time attentive network (DeF…