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Automatic time-frequency analysis of echolocation signals using the matched Gaussian multitaper spectrogram

Sandsten, Maria LU ; Reinhold, Isabella LU and Starkhammar, Josefin LU (2017) In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2017-August. p.3048-3052
Abstract

High-resolution time-frequency (TF) images of multi-component signals are of great interest for visualization, feature extraction and estimation. The matched Gaussian multitaper spectrogram has been proposed to optimally resolve multi-component transient functions of Gaussian shape. Hermite functions are used as multitapers and the weights of the different spectrogram functions are optimized. For a fixed number of multitapers, the optimization gives the approximate Wigner distribution of the Gaussian shaped function. Increasing the number of multitapers gives a better approximation, i.e. a better resolution, but the cross-terms also become more prominent for close TF components. In this submission, we evaluate a number of different... (More)

High-resolution time-frequency (TF) images of multi-component signals are of great interest for visualization, feature extraction and estimation. The matched Gaussian multitaper spectrogram has been proposed to optimally resolve multi-component transient functions of Gaussian shape. Hermite functions are used as multitapers and the weights of the different spectrogram functions are optimized. For a fixed number of multitapers, the optimization gives the approximate Wigner distribution of the Gaussian shaped function. Increasing the number of multitapers gives a better approximation, i.e. a better resolution, but the cross-terms also become more prominent for close TF components. In this submission, we evaluate a number of different concentration measures to automatically estimate the number of multitapers resulting in the optimal spectrogram for TF images of dolphin echolocation signals. The measures are evaluated for different multi-component signals and noise levels and a suggestion of an automatic procedure for optimal TF analysis is given. The results are compared to other well known TF estimation algorithms and examples of real data measurements of echolocation signals from a beluga whale (Delphinapterus leucas) are presented.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Concentration measures, Dolphin echolocation signals, Multi-component signals, Time-frequency analysis
in
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
volume
2017-August
pages
5 pages
external identifiers
  • scopus:85039147311
ISSN
2308-457X
DOI
10.21437/Interspeech.2017-119
language
English
LU publication?
yes
id
06a16ee6-1059-4dcd-bb1b-71271ce7e6ea
date added to LUP
2018-01-08 13:29:17
date last changed
2018-01-08 13:29:17
@article{06a16ee6-1059-4dcd-bb1b-71271ce7e6ea,
  abstract     = {<p>High-resolution time-frequency (TF) images of multi-component signals are of great interest for visualization, feature extraction and estimation. The matched Gaussian multitaper spectrogram has been proposed to optimally resolve multi-component transient functions of Gaussian shape. Hermite functions are used as multitapers and the weights of the different spectrogram functions are optimized. For a fixed number of multitapers, the optimization gives the approximate Wigner distribution of the Gaussian shaped function. Increasing the number of multitapers gives a better approximation, i.e. a better resolution, but the cross-terms also become more prominent for close TF components. In this submission, we evaluate a number of different concentration measures to automatically estimate the number of multitapers resulting in the optimal spectrogram for TF images of dolphin echolocation signals. The measures are evaluated for different multi-component signals and noise levels and a suggestion of an automatic procedure for optimal TF analysis is given. The results are compared to other well known TF estimation algorithms and examples of real data measurements of echolocation signals from a beluga whale (Delphinapterus leucas) are presented.</p>},
  author       = {Sandsten, Maria and Reinhold, Isabella and Starkhammar, Josefin},
  issn         = {2308-457X},
  keyword      = {Concentration measures,Dolphin echolocation signals,Multi-component signals,Time-frequency analysis},
  language     = {eng},
  pages        = {3048--3052},
  series       = {Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH},
  title        = {Automatic time-frequency analysis of echolocation signals using the matched Gaussian multitaper spectrogram},
  url          = {http://dx.doi.org/10.21437/Interspeech.2017-119},
  volume       = {2017-August},
  year         = {2017},
}