Title :
Classification of whale vocalizations using the Weyl transform
Author :
Yin Xian ; Thompson, Andrew ; Qiang Qiu ; Nolte, Loren ; Nowacek, Douglas ; Jianfeng Lu ; Calderbank, Robert
Author_Institution :
Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
Abstract :
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.
Keywords :
feature extraction; polynomials; signal classification; signal reconstruction; transforms; MFCC; Weyl transform; chirplet transform; feature extraction; marine mammals vocalization; polynomial; signal reconstruction; signals global information; whale vocalizations classification; Chirp; Feature extraction; Mel frequency cepstral coefficient; Polynomials; Time-frequency analysis; Transforms; Whales; Weyl transform; parameter estimation; polynomial phase; whale classification;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178074