Journal of Electrical Engineering and Renewable Energies Development
Volume 2, Numéro 2, Pages 54-59
2026-07-12

Packet Loss Concealment Using Deep Neural Networks For Cs-celp-type Speech Coders In Voip



Authors : Bakri Adil . Khaouani Boumediene . Berrabah Djamaleddine .

Abstract

Packet loss in Voice over Internet Protocol (VoIP) communications can significantly degrade speech quality, particularly affecting Conjugate-Structure Code-Excited Linear Prediction (CS-CELP) type speech coders like G.729. Traditional Packet Loss Concealment (PLC) methods often struggle with consecutive frame losses. Recent advancements in deep learning have introduced Deep Neural Networks (DNNs) as a promising solution for PLC. This paper proposes a Deep Neural Network (DNN)-based Packet Loss Concealment (PLC) algorithm for CS-CELP speech coders, specifically targeting the G.729 codec under packet-loss conditions.

Keywords

Voice Internet Protocol (VoIP), CS-CELP, Coder G.729, Packet Loss Concealment, Deep Neural Network, Packet Loss,

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