Wavelet De-noising with Independent Component Analysis for Segmentation of Dolphin Whistles in a Noisy Underwater Environment

Abstract

Bottlenose dolphins (Tursiops truncatus) are the most widely studied species of dolphin and are known to produce a complex mixture of different types of sounds. They are believed to communicate through frequency-modulated pure tones (whistles), and produce broadband clicks or click trains for echolocation while investigating their environment. They also produce a large range of other types of sounds variously described as barks, grunts, groans, etc. To further our aim of 2-way acoustically mediated communication with dolphins to study dolphin cognition, we need to separate Bottlenose dolphin whistles from noisy underwater recordings, which not only consist of whistles, but also broadband echolocation clicks, water splashes and other sources of ambient noise. Independent component analysis (ICA) has been successfully used for the separation of independent sound sources in many applications. In this paper we will discuss the use of ICA to separate dolphin whistles from other underwater sound sources.