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Paper Abstract and Keywords
Presentation 2026-04-10 13:00
Hybrid Packet Loss Concealment for Ensemble Audio Using Frequency Feature Processing Based on Spectral Structure
Katsuori Takeuchi, Ryo Yamamoto, Satoshi Ohzahata (UEC) NS2026-15
Abstract (in Japanese) (See Japanese page) 
(in English) In the real-time transmission of high-quality audio signals, Packet Loss Concealment (PLC) technology has gained significant attention.
This technology reconstruct lost signals at the receiver side using only correctly received packet, thereby reducing the impact of packet loss on the reproduced sound.
As an example, previous research proposed PARCNet as a hybrid PLC method that integrates Linear Predictive Coding (LPC) and Deep Neural Networks (DNN).
However, previous research is limited to the training and evaluation of single-instrument sound sources.
Consequently, restoration performance may significantly decrease for ensemble sound sources that contain complex spectral changes and composite harmonic components.
To address this issue, this paper proposes a hybrid PLC method that performs frequency information processing based on spectral structures.
This method aim to achieve auditorily natural and high-precision restoration for ensemble sound sources for more practical utilization of PLC technology.
The proposed method introduces pre-processing steps for the deep learning input data: the integration of neighboring frequencies, band-split processing based on human auditory characteristics, and integrative processing of inter-band information.
Comparative experiments with previous research demonstrate that the proposed method is effective for the restoration of spectral structures such as attack sounds and harmonic components.
Keyword (in Japanese) (See Japanese page) 
(in English) Packet Loss Concealment / Band-Split / Deep learning / / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 2, NS2026-15, pp. 81-86, April 2026.
Paper # NS2026-15 
Date of Issue 2026-04-02 (NS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NS2026-15

Conference Information
Committee NS  
Conference Date 2026-04-09 - 2026-04-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Yakushima Island Environmental and Cultural Village Center + Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication traffic theory, Traffic and quality evaluation, Network performance evaluation, QoS/QoE, Reliability and robustness, Traffic and quality management, AI and machine learning, Network and system operation management, High capacity, low latency, many connections, General 
Paper Information
Registration To NS 
Conference Code 2026-04-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Hybrid Packet Loss Concealment for Ensemble Audio Using Frequency Feature Processing Based on Spectral Structure 
Sub Title (in English)  
Keyword(1) Packet Loss Concealment  
Keyword(2) Band-Split  
Keyword(3) Deep learning  
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1st Author's Name Katsuori Takeuchi  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Ryo Yamamoto  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Satoshi Ohzahata  
3rd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2026-04-10 13:00:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2026-15 
Volume (vol) vol.126 
Number (no) no.2 
Page pp.81-86 
#Pages 6 
Date of Issue 2026-04-02 (NS) 

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