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Paper Abstract and Keywords
Presentation 2019-12-06 13:55
[Poster Presentation] Time-Varying Complex AR speech analysis based on l2-norm regularization
Keiichi Funaki (Univ. of the Ryukyus) SP2019-41
Abstract (in Japanese) (See Japanese page) 
(in English) Linear prediction (LP) is a mathematical operation estimating an all-pole spectrum from the speech
signal. It is an essential methodology in speech coding since LP coefficients can be determined using a small
amount of computation and quantized efficiently using vector quantization (VQ). l2-norm regularized LP (RLP)
and context-aware time-regularized LP (TRLP) analysis have been proposed and shown to improve performance.
The former one suppresses rapid spectral changes in the frequency domain and the latter one suppresses the rapid
spectral changes in the time domain. In our previous study, we proposed the MMSE-based time-varying complex
AR (TV-CAR) speech analysis that is the complex and time-varying version of the LP and recently offered the
RLP-based TV-CAR analysis. In this paper, we propose the novel l2-norm regularized TV-CAR analysis based on
not only the TRLP but also the RLP, and the objective evaluation using F0 estimation applied with the estimated
complex residual signals shows that the proposed method performs best.
Keyword (in Japanese) (See Japanese page) 
(in English) AR speech analysis / time-varying and complex analysis / l2-norm regularization / time-regularized LP / F0 estimation / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 321, SP2019-41, pp. 73-77, Dec. 2019.
Paper # SP2019-41 
Date of Issue 2019-11-29 (SP) 
ISSN Print edition: ISSN 0913-5685  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)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
Download PDF SP2019-41

Conference Information
Committee NLC IPSJ-NL SP IPSJ-SLP  
Conference Date 2019-12-04 - 2019-12-06 
Place (in Japanese) (See Japanese page) 
Place (in English) NHK Science & Technology Research Labs. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 6th Natural Language Processing Symposium & The 21th Spoken Language Symposium 
Paper Information
Registration To SP 
Conference Code 2019-12-NLC-NL-SP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Time-Varying Complex AR speech analysis based on l2-norm regularization 
Sub Title (in English)  
Keyword(1) AR speech analysis  
Keyword(2) time-varying and complex analysis  
Keyword(3) l2-norm regularization  
Keyword(4) time-regularized LP  
Keyword(5) F0 estimation  
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1st Author's Name Keiichi Funaki  
1st Author's Affiliation University of the Ryukyus (Univ. of the Ryukyus)
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Speaker
Date Time 2019-12-06 13:55:00 
Presentation Time 90 
Registration for SP 
Paper # IEICE-SP2019-41 
Volume (vol) IEICE-119 
Number (no) no.321 
Page pp.73-77 
#Pages IEICE-5 
Date of Issue IEICE-SP-2019-11-29 


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