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Daniele Mirabilii

Daniele Mirabilii
WSAudiology

Master of Science
PhD candidate - Development Engineer

About

11
Publications
1,054
Reads
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30
Citations
Citations since 2017
11 Research Items
30 Citations
20172018201920202021202220230246810
20172018201920202021202220230246810
20172018201920202021202220230246810
20172018201920202021202220230246810
Introduction
D. Mirabilii (B.Sc. in Electronic Engineering - La Sapienza University of Rome) (M.Sc. in Computer Science/Sound and Music Engineering - Politecnico di Milano). In 2018, he joined the International Audio Laboratories of Erlangen (a joint institution of the FAU Erlangen-Nürnberg and Fraunhofer IIS) as a PhD candidate. His research interests are in the area of audio signal processing, with particular focus on multichannel wind noise analysis, synthesis and processing.
Additional affiliations
Friedrich-Alexander-University of Erlangen-Nürnberg
Position
  • Research Assistant

Publications

Publications (11)
Conference Paper
Full-text available
A novel multi-channel artificial wind noise generator based on a fluid dynamics model, namely the Corcos model, is proposed. In particular, the model is used to approximate the complex coherence function of wind noise signals measured with closely-spaced microphones in the free-field and for time-invariant wind stream direction and speed. Prelimina...
Article
Outdoor recording is particularly challenging in the presence of wind, which induces highly non-stationary noise in the microphone signals. To enhance a desired signal, e.g., speech, a dedicated noise reduction processing is required. The reduction is usually performed by estimating an unknown set of parameters, e.g., the noise and the speech power...
Article
The spatial properties of a noise field can be described by a spatial coherence function. Synthetic multichannel noise signals exhibiting a specific spatial coherence can be generated by properly mixing a set of uncorrelated, possibly non-stationary, signals. The mixing matrix can be obtained by decomposing the spatial coherence matrix. As proposed...
Conference Paper
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 wind noise while limiting the spatial distortions of...
Article
Wind-induced noise recorded with a compact microphone array can be exploited to infer the mean velocity of the free-field airflow. In this work, a model-based method to estimate the wind flow speed and direction is proposed that uses spectro-spatial correlations of closely spaced microphone signals. As shown in a recent work by the present authors,...
Conference Paper
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 small aperture array are exploited, i.e., the low-frequency spatial coherence of wind noise signals is used as an input feature. The output is an estimate of the wind...
Conference Paper
Full-text available
Outdoor recordings of speech are often corrupted by wind noise, which is difficult to reduce due to its high non-stationarity. In this work, a multi-channel wind noise reduction method is presented, based on a joint estimation of the speech and wind noise power spectral densities. In contrast to existing methods that assume un-correlated wind noise...
Preprint
Full-text available
The difference-to-sum power ratio was proposed and used to suppress wind noise under specific acoustic conditions. In this contribution, a general formulation of the difference-to-sum power ratio associated with a mixture of speech and wind noise is proposed and analyzed. In particular, it is assumed that the complex coherence of convective turbule...
Preprint
Full-text available
A novel multi-channel artificial wind noise generator based on a fluid dynamics model, namely the Corcos model, is proposed. In particular, the model is used to approximate the complex coherence function of wind noise signals measured with closely-spaced microphones in the free-field and for time-invariant wind stream direction and speed. Prelimina...

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