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Article

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Title

A Survey on Low-Latency DNN-Based Speech Enhancement

Authors

[ 1 ] Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics, electrical engineering and space technology

Year of publication

2023

Published in

Sensors

Journal year: 2023 | Journal volume: vol. 23 | Journal number: iss. 3

Article type

scientific article

Publication language

english

Keywords
EN
  • low-latency speech enhancement
  • DNN
  • computational cost
Abstract

EN This paper presents recent advances in low-latency, single-channel, deep neural network-based speech enhancement systems. The sources of latency and their acceptable values in different applications are described. This is followed by an analysis of the constraints imposed on neural network architectures. Specifically, the causal units used in deep neural networks are presented and discussed in the context of their properties, such as the number of parameters, the receptive field, and computational complexity. This is followed by a discussion of techniques used to reduce the computational complexity and memory requirements of the neural networks used in this task. Finally, the techniques used by the winners of the latest speech enhancement challenges (DNS, Clarity) are shown and compared.

Date of online publication

26.01.2023

Pages (from - to)

1380-1 - 1380-26

DOI

10.3390/s23031380

URL

https://www.mdpi.com/1424-8220/23/3/1380

Comments

Article Number: 1380

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

100

Impact Factor

3,4

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