4 accepted papers
Neuromorphic computing, inspired by nervous systems, revolutionizes information processing with its focus on efficiency and low power consumption. Using sparse coding, this paradigm enhances processing efficiency, which is crucial for edge devices with power constraints. The Locally Competitive Algo…
The auditory system is extremely efficient in extracting attended auditory information in the presence of competing speakers. Single-channel speech enhancement algorithms, however, greatly lack this efficacy. In this paper, we propose a novel deep learning method referred to as the Brain Enhanced Sp…
In this paper, we introduce a discriminative training algorithm of the non-negative matrix factorization (NMF) model for single-channel enhancement of convolutive noisy speech. The basis vectors for the clean speech and noises are estimated simultaneously during the training stage by incorporating t…
In this paper, we propose a basis compensation algorithm for non-negative matrix factorization (NMF) models as applied to supervised single-channel speech enhancement. In the proposed framework, we use extra free basis vectors for both the clean speech and noise during the enhancement stage in order…