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DOI: 10.14569/IJACSA.2024.01504126
PDF

Packet Loss Concealment Estimating Residual Errors of Forward-Backward Linear Prediction for Bone-Conducted Speech

Author 1: Ohidujjaman
Author 2: Nozomiko Yasui
Author 3: Yosuke Sugiura
Author 4: Tetsuya Shimamura
Author 5: Hisanori Makinae

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 4, 2024.

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Abstract: This study proposes a suitable model for packet loss concealment (PLC) by estimating the residual error of the linear prediction (LP) method for bone-conducted (BC) speech. Instead of conventional LP-based PLC techniques where the residual error is ignored, we employ forward-backward linear prediction (FBLP), known as the modified covariance (MC) method, by incorporating the residual error estimates. The MC method provides precise LP estimation for a short data length, reduces the numerical difficulties, and produces a stable model, whereas the conventional autocorrelation (ACR) method of LP suffers from numerical problems. The MC method has the effect of compressing the spectral dynamic range of the BC speech, which improves the numerical difficulties. Simulation results reveal that the proposed method provides excellent outcomes from some objective evaluation scores in contrast to conventional PLC techniques.

Keywords: Autocorrelation method; bone-conducted speech; modified covariance method; packet loss concealment; residual error

Ohidujjaman , Nozomiko Yasui, Yosuke Sugiura, Tetsuya Shimamura and Hisanori Makinae, “Packet Loss Concealment Estimating Residual Errors of Forward-Backward Linear Prediction for Bone-Conducted Speech” International Journal of Advanced Computer Science and Applications(IJACSA), 15(4), 2024. http://dx.doi.org/10.14569/IJACSA.2024.01504126

@article{2024,
title = {Packet Loss Concealment Estimating Residual Errors of Forward-Backward Linear Prediction for Bone-Conducted Speech},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01504126},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01504126},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {4},
author = {Ohidujjaman and Nozomiko Yasui and Yosuke Sugiura and Tetsuya Shimamura and Hisanori Makinae}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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