Complex Wavelet Based Modulation Analysis

Jean-Marc Luneau, Jérôme Lebrun, Søren Holdt Jensen

Research output: Contribution to journalConference article in JournalResearchpeer-review

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Abstract

Low-frequency modulation of sound carry important information for speech and music. The modulation spectrum i commonly obtained by spectral analysis of the sole temporal envelopes of the sub-bands out of a time-frequency analysis. Processing in this domain usually creates undesirable distortions because only the magnitudes are taken into account and the phase data is often neglected. We remedy this problem with the use of a complex wavelet transform as a more appropriate envelope and phase processing tool. Complex wavelets carry both magnitude and phase explicitly with great sparsity and preserve well polynomial trends. Moreover an analytic Hilbert-like transform is possible with complex wavelets implemented as an orthogonal filter bank. By working in an alternative transform domain
coined as “Modulation Subbands”, this transform shows very promising denoising capabilities and suggests new approaches for joint spectro-temporal analytic processing of slow frequency and phase varying signals.
Original languageEnglish
JournalProc. of Asilomar Conference on Signals, Systems, and Computers
Number of pages5
ISSN1058-6393
Publication statusPublished - 2008
EventAsilomar Conference on Signals, Systems and Computers - Pacific Grove, Ca, United States
Duration: 26 Oct 200829 Oct 2008
Conference number: 42

Conference

ConferenceAsilomar Conference on Signals, Systems and Computers
Number42
CountryUnited States
CityPacific Grove, Ca
Period26/10/200829/10/2008

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Modulation
Processing
Frequency modulation
Spectrum analysis
Wavelet transforms
Acoustic waves

Cite this

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title = "Complex Wavelet Based Modulation Analysis",
abstract = "Low-frequency modulation of sound carry important information for speech and music. The modulation spectrum i commonly obtained by spectral analysis of the sole temporal envelopes of the sub-bands out of a time-frequency analysis. Processing in this domain usually creates undesirable distortions because only the magnitudes are taken into account and the phase data is often neglected. We remedy this problem with the use of a complex wavelet transform as a more appropriate envelope and phase processing tool. Complex wavelets carry both magnitude and phase explicitly with great sparsity and preserve well polynomial trends. Moreover an analytic Hilbert-like transform is possible with complex wavelets implemented as an orthogonal filter bank. By working in an alternative transform domaincoined as “Modulation Subbands”, this transform shows very promising denoising capabilities and suggests new approaches for joint spectro-temporal analytic processing of slow frequency and phase varying signals.",
author = "Jean-Marc Luneau and J{\'e}r{\^o}me Lebrun and Jensen, {S{\o}ren Holdt}",
year = "2008",
language = "English",
journal = "Asilomar Conference on Signals, Systems and Computers. Conference Record",
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Complex Wavelet Based Modulation Analysis. / Luneau, Jean-Marc; Lebrun, Jérôme; Jensen, Søren Holdt.

In: Proc. of Asilomar Conference on Signals, Systems, and Computers, 2008.

Research output: Contribution to journalConference article in JournalResearchpeer-review

TY - GEN

T1 - Complex Wavelet Based Modulation Analysis

AU - Luneau, Jean-Marc

AU - Lebrun, Jérôme

AU - Jensen, Søren Holdt

PY - 2008

Y1 - 2008

N2 - Low-frequency modulation of sound carry important information for speech and music. The modulation spectrum i commonly obtained by spectral analysis of the sole temporal envelopes of the sub-bands out of a time-frequency analysis. Processing in this domain usually creates undesirable distortions because only the magnitudes are taken into account and the phase data is often neglected. We remedy this problem with the use of a complex wavelet transform as a more appropriate envelope and phase processing tool. Complex wavelets carry both magnitude and phase explicitly with great sparsity and preserve well polynomial trends. Moreover an analytic Hilbert-like transform is possible with complex wavelets implemented as an orthogonal filter bank. By working in an alternative transform domaincoined as “Modulation Subbands”, this transform shows very promising denoising capabilities and suggests new approaches for joint spectro-temporal analytic processing of slow frequency and phase varying signals.

AB - Low-frequency modulation of sound carry important information for speech and music. The modulation spectrum i commonly obtained by spectral analysis of the sole temporal envelopes of the sub-bands out of a time-frequency analysis. Processing in this domain usually creates undesirable distortions because only the magnitudes are taken into account and the phase data is often neglected. We remedy this problem with the use of a complex wavelet transform as a more appropriate envelope and phase processing tool. Complex wavelets carry both magnitude and phase explicitly with great sparsity and preserve well polynomial trends. Moreover an analytic Hilbert-like transform is possible with complex wavelets implemented as an orthogonal filter bank. By working in an alternative transform domaincoined as “Modulation Subbands”, this transform shows very promising denoising capabilities and suggests new approaches for joint spectro-temporal analytic processing of slow frequency and phase varying signals.

M3 - Conference article in Journal

JO - Asilomar Conference on Signals, Systems and Computers. Conference Record

JF - Asilomar Conference on Signals, Systems and Computers. Conference Record

SN - 1058-6393

ER -