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Spectral analysis of sperm whale vocalizations

Robey, Lynn LU (2024) In Bachelor's Thesis in Mathematical Sciences MASK11 20241
Mathematical Statistics
Abstract
Sperm whales (Physeter macrocephalus) communicate with one another using
an intricate language made up of sequences of clicks. Recent studies have
begun to dig deeper into the structure and content of these vocalisations in an
effort to detect and extract significant patterns and features. Whether or not
the results of such research will eventually allow us to translate sperm whale
speech into something akin to a human language is a subject of debate. Regardless
of the ultimate outcome, the insight is of interest to many scientific
fields, including conservation biology and bio-inspired engineering. For this
project, over 1400 audio clips recorded between 1952 and 1995 were processed
in order to isolate clicks from background... (More)
Sperm whales (Physeter macrocephalus) communicate with one another using
an intricate language made up of sequences of clicks. Recent studies have
begun to dig deeper into the structure and content of these vocalisations in an
effort to detect and extract significant patterns and features. Whether or not
the results of such research will eventually allow us to translate sperm whale
speech into something akin to a human language is a subject of debate. Regardless
of the ultimate outcome, the insight is of interest to many scientific
fields, including conservation biology and bio-inspired engineering. For this
project, over 1400 audio clips recorded between 1952 and 1995 were processed
in order to isolate clicks from background noise. Frequency analysis on over
5000 detected clicks yielded dominant frequencies in the range of 2 kHz to 10
kHz with varying frequency distributions. It was possible to group the clicks
into distinct categories based on their frequency contents, dominant frequencies,
and number of strongly represented frequencies. This paper illustrates
the performance of methods for automatically detecting click onsets in noisy
data, as well as an effective approach for fitting an estimated signal envelope
to clicks based on a Gumbel probability density function. Several patterns
in the spectral features of sperm whale clicks were identified. The recurring
patterns in the value and number of dominant frequencies in each click suggest
the existence of multiple distinct click types, and several examples of
potential click categories are described in this paper. There also appears to
be a noteworthy relationship between the geographical location, dominant
frequency, and spectral envelope parameters of clicks. Further studies will
be necessary to validate and refine the results described here, which suggest
that sperm whale vocalizations consist of a more rich and complex combinatorial
structure than has previously been described and that this structure
varies systematically between geographical locations. (Less)
Please use this url to cite or link to this publication:
author
Robey, Lynn LU
supervisor
organization
course
MASK11 20241
year
type
M2 - Bachelor Degree
subject
keywords
Spectral analysis, frequency analysis, spectral envelope, sperm whale, animal communication
publication/series
Bachelor's Thesis in Mathematical Sciences
report number
LUNFMS-4073-2024
ISSN
1654-6229
other publication id
2024:K7
language
English
id
9159350
date added to LUP
2024-06-11 12:58:18
date last changed
2024-06-11 12:58:18
@misc{9159350,
  abstract     = {{Sperm whales (Physeter macrocephalus) communicate with one another using
an intricate language made up of sequences of clicks. Recent studies have
begun to dig deeper into the structure and content of these vocalisations in an
effort to detect and extract significant patterns and features. Whether or not
the results of such research will eventually allow us to translate sperm whale
speech into something akin to a human language is a subject of debate. Regardless
of the ultimate outcome, the insight is of interest to many scientific
fields, including conservation biology and bio-inspired engineering. For this
project, over 1400 audio clips recorded between 1952 and 1995 were processed
in order to isolate clicks from background noise. Frequency analysis on over
5000 detected clicks yielded dominant frequencies in the range of 2 kHz to 10
kHz with varying frequency distributions. It was possible to group the clicks
into distinct categories based on their frequency contents, dominant frequencies,
and number of strongly represented frequencies. This paper illustrates
the performance of methods for automatically detecting click onsets in noisy
data, as well as an effective approach for fitting an estimated signal envelope
to clicks based on a Gumbel probability density function. Several patterns
in the spectral features of sperm whale clicks were identified. The recurring
patterns in the value and number of dominant frequencies in each click suggest
the existence of multiple distinct click types, and several examples of
potential click categories are described in this paper. There also appears to
be a noteworthy relationship between the geographical location, dominant
frequency, and spectral envelope parameters of clicks. Further studies will
be necessary to validate and refine the results described here, which suggest
that sperm whale vocalizations consist of a more rich and complex combinatorial
structure than has previously been described and that this structure
varies systematically between geographical locations.}},
  author       = {{Robey, Lynn}},
  issn         = {{1654-6229}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Bachelor's Thesis in Mathematical Sciences}},
  title        = {{Spectral analysis of sperm whale vocalizations}},
  year         = {{2024}},
}