Linear acoustic echo cancellation using deep neural networks and convex reconstruction of incomplete transfer function

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F17%3A00004534" target="_blank" >RIV/46747885:24220/17:00004534 - isvavai.cz</a>

Result on the web

<a href="https://asap.ite.tul.cz/wp-content/uploads/sites/3/2017/06/ECMSM2017.pdf" target="_blank" >https://asap.ite.tul.cz/wp-content/uploads/sites/3/2017/06/ECMSM2017.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ECMSM.2017.7945913" target="_blank" >10.1109/ECMSM.2017.7945913</a>

Result language

angličtina

Original language name

Linear acoustic echo cancellation using deep neural networks and convex reconstruction of incomplete transfer function

Original language description

Linear acoustic path estimation for acoustic echo cancellation is difficult during periods where the near-end signal (speech) is active. In this paper, we assume that the impulse response is sparse. There are many algorithms that solve the problem of estimating sparse impulse response in the time domain. In this paper, we propose algorithms working in the time-frequency domain. In our approach, it is assumed that the respective transfer function can be estimated only for those frequencies where the near-end signal is not active. First, a deep neural network trained on mixed signals is used to detect the activity of the near-end signal. In frequencies where no activity is detected, the acoustic transfer function is estimated using conventional frequency domain least squares. This results in an incomplete transfer function (ITF) estimate. The completion is done through finding the sparsest representation of the ITF in the time domain. This can be done adaptively using the soft-threshold function, which is applied in the time domain. To achieve improved accuracy, oversampling can be used.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA14-11898S" target="_blank" >GA14-11898S: Semi-blind methods in speech enhancement with microphone arrays</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their Application to Mechatronics, ECMSM 2017

ISBN

978-1-5090-5582-1

ISSN

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e-ISSN

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Number of pages

6

Pages from-to

1-6

Publisher name

Institute of Electrical and Electronics Engineers Inc.

Place of publication

Donostia, San Sebastian, Spain

Event location

Donostia, San Sebastian, Spain

Event date

Jan 1, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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