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Edwin Mabande

3 accepted papers

2024

Ultra Low Complexity Deep Learning Based Noise Suppression

ICASSP 2024accepted

This paper introduces an innovative method for reducing the computational complexity of deep neural networks in real-time speech enhancement on resource-constrained devices. The proposed approach utilizes a two-stage processing framework, employing channelwise feature reorientation to reduce the com…

Cited by 0SourceScholar
2016

Towards robust close-talking microphone arrays for noise reduction in mobile phones

ICASSP 2016accepted

Adaptive close-talking differential microphone arrays (ACT-MAs) inherently suppress farfield noise while emphasizing desired nearfield signals. This paper discusses the applicability of ACT-MAs for noise reduction in mobile phones. In order to utilize the advantages of ACTMAs, we need to improve the…

Cited by 0SourceScholar
2015

A state-space partitioned-block adaptive filter for echo cancellation using inter-band correlations in the Kalman gain computation

ICASSP 2015accepted

A partitioned-block-based architecture for a model-based acoustic echo canceller in the frequency domain was recently presented. Partitioned-block-based frequency domain adaptive filters provide a lower algorithmic delay compared to the non-partitioned formulations, which is achieved by partitioning…

Cited by 8SourceScholar