Revisiting the Linear Prediction Analysis-by-Synthesis Speech Coding Paradigm Using Real-Time Convex Optimization

Daniele Giacobello, Manohar Murthi, Tobias Lindstrom Jensen, Mads Grasboll Christensen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, we propose a novel approach to speech coding by rewriting the nonlinear analysis-by-synthesis linear prediction scheme as a convex problem. This allows for determining trade-offs between, on one hand, the reconstruction error and, on the other, the sparsity of the predictor and the residual used to parametrize the speech signal. Differently from traditional coding schemes where the parameters are chosen throughout multiple optimization stages, our scheme produces a one-shot parametrization of a speech segment that intrinsically takes into consideration the voiced or unvoiced nature of a speech segment providing a better balance between residual and predictor and, consequently, a more appropriate bit allocation.

Original languageEnglish (US)
Title of host publicationConference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1947-1952
Number of pages6
ISBN (Electronic)9781538692189
DOIs
StatePublished - Feb 19 2019
Event52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States
Duration: Oct 28 2018Oct 31 2018

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2018-October
ISSN (Print)1058-6393

Conference

Conference52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
CountryUnited States
CityPacific Grove
Period10/28/1810/31/18

Fingerprint

Speech coding
Convex optimization
Nonlinear analysis

Keywords

  • convex optimization
  • real-time implementation
  • Sparse linear prediction
  • speech coding

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this

Giacobello, D., Murthi, M., Jensen, T. L., & Christensen, M. G. (2019). Revisiting the Linear Prediction Analysis-by-Synthesis Speech Coding Paradigm Using Real-Time Convex Optimization. In M. B. Matthews (Ed.), Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 (pp. 1947-1952). [8645448] (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2018-October). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2018.8645448

Revisiting the Linear Prediction Analysis-by-Synthesis Speech Coding Paradigm Using Real-Time Convex Optimization. / Giacobello, Daniele; Murthi, Manohar; Jensen, Tobias Lindstrom; Christensen, Mads Grasboll.

Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. ed. / Michael B. Matthews. IEEE Computer Society, 2019. p. 1947-1952 8645448 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2018-October).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Giacobello, D, Murthi, M, Jensen, TL & Christensen, MG 2019, Revisiting the Linear Prediction Analysis-by-Synthesis Speech Coding Paradigm Using Real-Time Convex Optimization. in MB Matthews (ed.), Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018., 8645448, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2018-October, IEEE Computer Society, pp. 1947-1952, 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018, Pacific Grove, United States, 10/28/18. https://doi.org/10.1109/ACSSC.2018.8645448
Giacobello D, Murthi M, Jensen TL, Christensen MG. Revisiting the Linear Prediction Analysis-by-Synthesis Speech Coding Paradigm Using Real-Time Convex Optimization. In Matthews MB, editor, Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. IEEE Computer Society. 2019. p. 1947-1952. 8645448. (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2018.8645448
Giacobello, Daniele ; Murthi, Manohar ; Jensen, Tobias Lindstrom ; Christensen, Mads Grasboll. / Revisiting the Linear Prediction Analysis-by-Synthesis Speech Coding Paradigm Using Real-Time Convex Optimization. Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. editor / Michael B. Matthews. IEEE Computer Society, 2019. pp. 1947-1952 (Conference Record - Asilomar Conference on Signals, Systems and Computers).
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