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Italian Workshop on Neural Nets

WIRN 2017 2017: Neural Advances in Processing Nonlinear Dynamic Signals pp 37–47Cite as

Neural Beamforming for Speech Enhancement: Preliminary Results

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 102))

Abstract

In the field of multi-channel speech quality enhancement, beamforming algorithms play a key role, being able to reduce noise and reverberation by spatial filtering. To that extent, an accurate knowledge of the Direction of Arrival (DOA) is crucial for the beamforming to be effective. This paper reports extremely improved DOA estimates with the use of a recently introduced neural DOA estimation technique, when compared to a reference algorithm such as Multiple Signal Classification (MUSIC). These findings motivated for the evaluation of beamforming with neural DOA estimation in the field of speech enhancement. By using the neural DOA estimation in conjunction with beamforming, speech signals affected by reverberation and noise improve their quality. These first findings are reported to be taken as a reference for further works related to beamforming for speech enhancement.

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Notes

  1. 1.

    https://www.audiolabs-erlangen.de/fau/professor/habets/software/rir-generator.

  2. 2.

    http://www.itu.int/rec/T-REC-P.862/en.

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Acknowledgements

We acknowledge the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support.

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche, 60131, Ancona, Italy

    Stefano Tomassetti, Leonardo Gabrielli, Emanuele Principi, Daniele Ferretti & Stefano Squartini

Authors
  1. Stefano Tomassetti
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  2. Leonardo Gabrielli
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  3. Emanuele Principi
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  4. Daniele Ferretti
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  5. Stefano Squartini
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Corresponding author

Correspondence to Leonardo Gabrielli .

Editor information

Editors and Affiliations

  1. Dipartimento di Psicologia, Università della Campana Luigi Vanvitelli, Caserta, Italy

    Anna Esposito

  2. Fundació Tecnocampus, Pompeu Fabra University, Mataro, Barcelona, Spain

    Marcos Faundez-Zanuy

  3. Department of Civil, Environmental, Energy, and Material Engineering, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Laboratorio di Neuronica, Dipartimento Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy

    Eros Pasero

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Tomassetti, S., Gabrielli, L., Principi, E., Ferretti, D., Squartini, S. (2019). Neural Beamforming for Speech Enhancement: Preliminary Results. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Advances in Processing Nonlinear Dynamic Signals. WIRN 2017 2017. Smart Innovation, Systems and Technologies, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-319-95098-3_4

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