Abstract
Whale sounds may mix several elements including whistle, click, and creak in the same vocalization, which may overlap in time and frequency, so it leads to conventional signal separation techniques challenging to be applied for the signal extraction. Unlike conventional signal separation techniques which are based on the frequency bands, such as WT and EMD, tunable-Q wavelet transform (TQWT) can separate the objected signal into particular components with different structures according to its oscillation property and eliminate in-band noise using the basis pursuit method. Considering the characteristics of oscillatory and transient impulse, we propose a novel signal separation method for whale whistle and click extraction. The proposed method is performed by the following two steps: first, TQWT is used to construct the dictionary for sparse representation. Secondly, the whale click and whistle construction are performed by designing the basis pursuit denoising (BPD) algorithm. The proposed method has been compared with one of the popular signal decomposition techniques, i.e., the EMD method. The experimental results show that the proposed method has a better performance of click and whistle signal separation in comparison with the EMD algorithm.
Highlights
Whale sounds are combined of several elements (whistle, regular click, and rapid-click buzzes) in the same vocalization [1]
Since the whistle and click signals have oscillatory and transient impulse characteristics, respectively, we proposed a sparse signal representation method with tunable-Q wavelet transform (TQWT) to extract click components with low Q factor and whistle components with high Q factor, respectively. e method is verified by the oceanic audio recording, and the results show effective extraction of click and whistle components from whale vocalization. e main contribution of this paper lies in (1) a new method that extracts click and whistle effectively and efficiently from multicomponents sound, (2) the selection of appropriate algorithm parameters in the actual application, and (3) the proposed method that can be used for other mammals to extract interesting component from the composite signal
We have proposed a sparse representation with TQWT method to extort the click and whistle components from the raw whale signal according to the oscillatory behavior of these two components
Summary
Whale sounds are combined of several elements (whistle, regular click, and rapid-click buzzes (creak)) in the same vocalization [1]. Whales utilize frequencymodulated pure tones (whistles) to communicate with each other. They emit transient impulses (clicks) to echolocate the targets and explore the environment. To further cognition of whale communication pattern and echolocation pattern, we need to separately extract whistles and clicks from the composite signal. Abundant methods have been presented to decompose multicomponent signals such as blind source separation [11], dual-tree complex wavelet transform [12], wavelet denoising, empirical mode decomposition (EMD) [13], ensemble empirical mode decomposition (EEMD), multiwavelet packet [14], and independent component analysis (ICA) [15,16,17,18]. Each component of the whale sounds may occupy the same frequency band and overlap in the frequency domain. us, the above methods cannot exactly extract each component from the whale sounds
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