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Daniele Mirabilii

3 accepted papers

2021

Direction Preserving Wind Noise Reduction Of B-Format Signals

ICASSP 2021accepted

Noise reduction in B-format recordings is particularly challenging as it concurrently requires to suppress undesired signals and preserve the spatial properties of the acoustic environment. In particular, wind noise poses an undesirable acoustic condition outdoors. In this work, methods to reduce wi…

Cited by 0SourceScholar
2020

Data-Driven Wind Speed Estimation Using Multiple Microphones

ICASSP 2020accepted

A deep neural network (DNN) based approach for estimating the speed of airflows using closely-spaced microphones is proposed. The spatial characteristics of wind noise measured with a smallaperture array are exploited, i.e., the low-frequency spatial coherence of wind noise signals is used as an inp…

Cited by 0SourceScholar