[Top] [All Lists]

Summary - Comparing Bird Songs

To: <>
Subject: Summary - Comparing Bird Songs
From: "Brian R. Mitchell" <>
Date: Fri, 5 Aug 2005 11:47:51 EDT
I received a number of responses to my post last week about comparing bird songs. Here is a summary of the responses, followed by my original post. I have not had a chance to follow up on these suggestions, but many of them look promising. Thanks for the terrific advice!

Adrian del Nevo reported that he is using STATISTICA's neural network module to perform these sorts of analyses: "We can 'train' the neural network to recognize similar patterns of songs and thus conduct the types of analyses you describe."

A few people (Arch McCallum, Tobias Riede, and Aisha Thorn) suggested looking into dynamic time warping. Papers included one by Dave Bradley and Rich Bradley in the 1970's on the Belding's Savannah Sparrow, and a paper by John Wiens comparing Sage Sparrow songs. There is also a 1998 paper in JASA 103(4):2185-96 that compares dynamic time warping and hidden Markov models. Another paper on dynamic time warping was: Tchernichovski, O., Nottebohm, F., Ho, C.E., Bijan, P., Mitra, P.P. (2000). A procedure for an automated measurement of song similarity. Animal Behaviour. 59, 1167-1176.

Ann Chen has used a genomics technique to analyze vocalization similarity in false killer whales. She used the Smith-Waterman algorithm, which is the backbone of BLAST, a tool used by genomics and proteomics researchers to compare sequences. The approach can account for similarities between phrase types and will output a distance matrix that can be used in a cluster analysis. She is currently working on a techniques paper that will publish her methods.

Diego Gil said that he has used Levenshtein distance to analyze willow warbler songs, and his analysis is reported in: Gil, Diego and Peter Slater. 2000. Song organisation and singing patterns of the Willow Warbler, Phylloscopus trochilus. Behaviour 137:759-782.

A couple of people (Jim Ingold and Ted Miller) suggested contacting Donald Kroodsma at U Mass or checking out his recent book: Kroodsma, D.E. (2005) The Singing Life of Birds. Houghton Mifflin.

Shaari Unger suggested checking out the work of Dr. John Ford at Canada Fisheries and Oceans on Orcinus orca vocalizations.

Greg Clark wrote that he had performed a similar analysis a few years ago, but that the technique he used was not particularly user friendly.

Jim Nollman has been using a program called Melodyne (owned by Celemony) to analyze recordings. The software's primary purpose is to analyze and repair music, but he thought that the software could conduct some interesting comparative analyses.2

I'm hoping someone on this list can point me to a technique for
analyzing similarity between bird songs (within a species).  Basically,
we have multiple songs recorded from about 20 bobolinks, and we want to
determine if songs recorded from individuals within a local area are
more similar than songs from different areas.  Bobolink songs are
complex, but are a sequence of phrases that are put together in
different ways by different individuals.

My question is whether there is a way to analyze a series of characters
for frequency and placement.  For instance we may have the following
three songs, where letters represent phrases:


Songs 1 and 2 share more phrases and start with the same phrases, so I
would classify them as being more similar.  Does anyone know of an
analytical technique for dealing with this sort of data?  I'm thinking
that the data is probably similar to some types of genetic data, where
letters would refer to alleles, and I'm also wondering if anyone has
applied genetic analysis methods to this type of data.

Brian R. Mitchell
Post-Doctoral Associate
University of Vermont
The Rubenstein School of Environment and Natural Resources
81 Carrigan Drive
Burlington, VT  05405-0088
(802) 656-2496


<Prev in Thread] Current Thread [Next in Thread>
  • Summary - Comparing Bird Songs, Brian R. Mitchell <=

The University of NSW School of Computer and Engineering takes no responsibility for the contents of this archive. It is purely a compilation of material sent by many people to the Bioacoustics-L mailing list. It has not been checked for accuracy nor its content verified in any way. If you wish to get material removed from the archive or have other queries about the archive e-mail Andrew Taylor at this address: andrewt@cse.unsw.EDU.AU