On Improving Error Resilience of Neural End-to-End Speech Coders

Fuente: arXiv
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Main Authors: Gupta, Kishan, Pia, Nicola, Korse, Srikanth, Brendel, Andreas, Fuchs, Guillaume, Multrus, Markus
Format: Preprint
Published: 2024
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_version_ 1866913851550728192
author Gupta, Kishan
Pia, Nicola
Korse, Srikanth
Brendel, Andreas
Fuchs, Guillaume
Multrus, Markus
author_facet Gupta, Kishan
Pia, Nicola
Korse, Srikanth
Brendel, Andreas
Fuchs, Guillaume
Multrus, Markus
contents Error resilient tools like Packet Loss Concealment (PLC) and Forward Error Correction (FEC) are essential to maintain a reliable speech communication for applications like Voice over Internet Protocol (VoIP), where packets are frequently delayed and lost. In recent times, end-to-end neural speech codecs have seen a significant rise, due to their ability to transmit speech signal at low bitrates but few considerations were made about their error resilience in a real system. Recently introduced Neural End-to-End Speech Codec (NESC) can reproduce high quality natural speech at low bitrates. We extend its robustness to packet losses by adding a low complexity network to predict the codebook indices in latent space. Furthermore, we propose a method to add an in-band FEC at an additional bitrate of 0.8 kbps. Both subjective and objective assessment indicate the effectiveness of proposed methods, and demonstrate that coupling PLC and FEC provide significant robustness against packet losses.
format Preprint
id arxiv_https___arxiv_org_abs_2406_08900
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On Improving Error Resilience of Neural End-to-End Speech Coders
Gupta, Kishan
Pia, Nicola
Korse, Srikanth
Brendel, Andreas
Fuchs, Guillaume
Multrus, Markus
Audio and Speech Processing
Sound
Signal Processing
Error resilient tools like Packet Loss Concealment (PLC) and Forward Error Correction (FEC) are essential to maintain a reliable speech communication for applications like Voice over Internet Protocol (VoIP), where packets are frequently delayed and lost. In recent times, end-to-end neural speech codecs have seen a significant rise, due to their ability to transmit speech signal at low bitrates but few considerations were made about their error resilience in a real system. Recently introduced Neural End-to-End Speech Codec (NESC) can reproduce high quality natural speech at low bitrates. We extend its robustness to packet losses by adding a low complexity network to predict the codebook indices in latent space. Furthermore, we propose a method to add an in-band FEC at an additional bitrate of 0.8 kbps. Both subjective and objective assessment indicate the effectiveness of proposed methods, and demonstrate that coupling PLC and FEC provide significant robustness against packet losses.
title On Improving Error Resilience of Neural End-to-End Speech Coders
topic Audio and Speech Processing
Sound
Signal Processing
url https://arxiv.org/abs/2406.08900