Classification of whale vocalizations using the Weyl transform

Yin Xian, Andrew Thompson, Qiang Qiu, Loren Nolte, Douglas Nowacek, Jianfeng Lu, Robert Calderbank

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

3 Citations (Scopus)


In this paper, we apply the Weyl transform to represent the vocalization of marine mammals. In contrast to other popular representation methods, such as the MFCC and the Chirplet transform, the Weyl transform captures the global information of signals. This is especially useful when the signal has low order polynomial phase. We can reconstruct the signal from the coefficients obtained from the Weyl transform, and perform classification based on these coefficients. Experimental results show that classification using features extracted from the Weyl transform outperforms the MFCC and the Chirplet transform on our collected whales data.
Original languageEnglish
Title of host publication2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Number of pages5
ISBN (Electronic)9781467369978
Publication statusPublished - 19 Apr 2015

Publication series

NameInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP)
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

User-Defined Keywords

  • whale classification
  • polynomial phase
  • parameter estimation
  • Weyl transform


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