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Is birdsong music? Evaluating harmonic intervals in songs of a Neotropical songbird


Abstract and Figures

Signals in animal communication are commonly judged as aesthetically appealing by human standards. This is particularly common for birdsong, often equated to musical compositions. No formal test, however, has analysed their harmonic properties. Musical intervals are based on the same physical characteristics of sound that underlie animal vocal signals. Thus, animals may use these intervals as rules to organize their vocalizations in a similar way as music. I tested a prediction derived from this hypothesis, that frequency ratios of adjacent notes in birdsong are closer to harmonic intervals than expected by chance. I determined to what degree the intervals created by adjacent notes of the song of nightingale wrens (Microcerculus philomela) conform to harmonic intervals. Songs from 81 birds across the entire distribution range of the species were analysed, comparing the intervals formed by adjacent notes to three different musical scales: chromatic, major diatonic and major pentatonic. Comparisons were made based on null model distributions. From 243 comparisons, only six (~2%) were significantly close to harmonic intervals, suggesting no consistent use of harmonic intervals. The frequency of the notes is the most varying song parameter in this species. If the frequencies are not determined by harmonic intervals in this species, it seems less likely that it happens in other birds with more complex song elements. Documented musical properties in birds might be caused by cultural biases of the listener or misunderstanding of the physics of musical compositions.
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Is birdsong music? Evaluating harmonic intervals in songs of a Neotropical
Marcelo Araya-Salas
Escuela de Biología, Universidad de Costa Rica, Ciudad Universitaria, Costa Rica
article info
Article history:
Received 4 December 2011
Initial acceptance 15 February 2012
Final acceptance 25 April 2012
Available online 6 June 2012
MS. number: A11-00965R
harmonic interval
Microcerculus philomela
musical scale
nightingale wren
Signals in animal communication are commonly judged as aesthetically appealing by human standards.
This is particularly common for birdsong, often equated to musical compositions. No formal test,
however, has analysed the harmonic properties of bird vocalizations. Musical intervals are based on the
same physical characteristics of sound that underlie animal vocal signals. Thus, animals may use these
intervals as rules to organize their vocalizations in a similar way as music. I tested a prediction derived
from this hypothesis, that frequency ratios of adjacent notes in birdsong are closer to harmonic intervals
than expected by chance. I determined to what degree the intervals created byadjacent notes of the song
of nightingale wrens, Microcerculus philomela, conform to harmonic intervals. I analysed songs from 81
birds across the entire distribution range of the species, comparing the intervals formed by adjacent
notes to three musical scales: chromatic, major diatonic and major pentatonic. Comparisons were made
based on null model distributions. From 243 comparisons, only six (w2%) were signicantly close to
harmonic intervals, suggesting no consistent use of harmonic intervals. The frequency of the notes is the
most varying song parameter in this species. If the frequencies are not determined by harmonic intervals
in this species, it seems less likely that it happens in other birds with more complex song elements.
Documented musical properties in birds might be caused by cultural biases of the listener or misun-
derstanding of the physics of musical compositions.
Ó2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.
Since ancient times, humans have judged animal signals by
human standards of beauty (Darwin 1871;Grammer et al. 2003).
This is particularly recurrent in the appreciation of birdsongs,
because of their resemblance to musical composition (Darwin
1871;Scholes 1938;Hartshorne 1958;Saunders 1959;Hall-
Craggs 1969;Dobson & Lemon 1977;West & King 1990;West
et al. 2004;Baptista & Keister 2005;Tierney et al. 2011). The
resemblance is due to the use of specic tonal qualities, pitch
relationships and phrase duration and rhythm in birdsongs (Marler
1969;Baptista 2004). The parallel between birdsong and music has
inspired many researchers and naturalists to equate the variation in
frequency found in birdsongs to their counterparts in musical
scales. For instance, Baptista & Keister (2005, page 432) in their
paper why birdsong is sometimes like musicwrote: Some bird-
song is pitched to the same scale as Western music, which is one
possible reason for human attraction to these sounds. Many other
examples can be found in ornithological literature: Saunders (1959)
suggested that white-throated sparrows, Zonotrichia albicollis,have
a perfect fourth (musical interval) between the rst and second
notes, Borror & Reese (1956, page 182) suggested that the songs of
the wood thrush, Hylocichla mustelina,are so pitched that they
follow our musical scale very accurately,Hartshorne (1973), that
the canyon wren, Catherpes mexicanus, sings in the chromatic scale
(musical scale with 12 pitches per octave), and Wing (1951), that
the hermit thrush, Catharus guttatus, sings in the pentatonic scale
(musical scale with ve pitches per octave).
Although the aforementioned accounts may be useful for
describing the pitch variation among song elements in birdsongs,
they imply that birds use discrete sound intervals, instead of
a continuous range of sounds, to organize their songs. If true, this
would have important implications for understanding the patterns
of song ontogeny and evolution in animal signals. However, that
hypothesis has not been properly tested for any bird species. To my
knowledge, the only study on this matter was made by Dobson &
Lemon (1977), who qualitatively compared the songs of white-
throated sparrows, Z.albicollis,and African boubou shrikes
(Laniarius sp.) with the most common Western musical scales.
Unfortunately, no statistical test was made and no clear insight was
provided on the harmonic properties of birdsongs.
Furthermore, no cogent rationale for the use of similar intervals
in music and birdsong has been proposed. Why should a bird use
*Correspondence and present address: M. Araya-Salas, Department of Biology,
New Mexico State University, 1615 Espina, Las Cruces, NM 88001, U.S.A.
E-mail address:
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Animal Behaviour 84 (2012) 309e313
the same intervals as musicians? Musicians use specic intervals
because of the consonance produced by the combination of their
sounds. This consonance comes from the physical properties of
instruments and human vocal tracts (Benson 2008). Stringed and
wind instruments and human vocal tracts produce a spectrum of
overtones along with a fundamental frequency for each note. In
both instruments and vocal tracts these overtones are harmonics,
which are dened as exact integer multiples of the fundamental
frequency (Benson 2008;Gill & Purves 2009). Different pitch notes
for which the frequencies are proportionally related share most of
their harmonics, which generates the consonance of their interval
(Benson 2008). In other words, musical intervals are formed by
sounds with a higher similarity in the frequencies of their harmonic
spectrum compared to nonmusical intervals. Thus, musical inter-
vals are based not in human conventional arrays of frequencies but
in the physical characteristics of the sounds. The preference in
humans may have evolved through a sensory bias towards intervals
reecting the spectral characteristics of conspecic vocalizations
(Gill & Purves 2009) or as a honest signal of cognitive abilities
favoured by sexual selection (Miller 2001). Similar hypotheses may
explain the evolution of analogous preferences in other animals
with comparable spectral complexity (see below). Several other
hypotheses have been proposed for the evolution of music in
humans and the present list is not exhaustive (Patel 2010).
Many species of birds, as well as mammals and amphibians,
generate harmonics proportionally related to the fundamental
frequency in their vocalizations in the same way as the musical
instruments we use (Bradbury & Vehrencamp 1998). In addition,
birds seem to have the necessary auditory and neural capacity to
relate harmonically linked sounds. Birds can perceive the harmonic
structure of single elements in their songs (Cynx et al. 1990;Lohr &
Dooling 1998;Doolinget al. 2002) and in some cases use it to encode
biologically relevant information (Morgan & Howse 1973;Aubin &
Bremond 1992). Some bird species even show relative pitch
discrimination as humans do and can discriminate pairs of notes by
their frequency ratios (Weary & Weisman 1991;Weisman et al.
1994;Bottoni et al. 2003). Overall, the available evidence suggests
that birds have the necessary abilities requiredto relate and organize
different song elements by the consonance of their frequencies, or in
other words, to conform songs to harmonic intervals.
Even though birdsongs might conform to harmonic scales, the
often complex and frequency-modulated structure of the song
elements has made the testing of this hypothesis difcult, basically
because it complicates the selection of a single frequency value as
representative of a particular element. Onlya few bird species seem
to have the adequate element structure and pitch variation
between elements to allow detailed analysis (Dobson & Lemon
1977). An ideal birdsong for analysis in terms of harmonic inter-
vals should have sounds of sustained and almost pure pitch
elements, a variety of frequencies among adjacent elements, and
clear harmonic structure to its elements. The nightingale wren,
Microcerculus philomela, represents an excellent opportunity to test
these ideas. Its song consists of a single stereotyped series of nearly
pure-tone notes at different pitches. The notes show clear harmonic
structure with roughly no pitch repetition among consecutive
notes (Fig. 1). This species also shows microgeographical song
variation with several dialects in an area of just a few kilometres
(M. Araya-Salas, T. F. Wright & G. Barrantes, unpublished data). The
geographical variation is due to different arrays of notes rather than
to variation in the structure of the composing elements (M. Araya-
Salas, T. F. Wright & G. Barrantes, unpublished data). This type of
variation allows us to test the existence of harmonic intervals in
several different arrays of notes. For this study, I tested the
prediction derived from the harmonic birdsong hypothesis, that the
frequency ratio of adjacent notes would be closer to harmonic
intervals than expected by chance. For this I use just intonation
FP8 P8P5 m7 M2 M3
Time (s)
Frequency (kHz)Amplitude (dB)
12 13 14 15 16 17 18 19
Figure 1. Spectrogram of a segment of the song of a nightingale wren from La Selva Biological Station, Costa Rica. The spectrogram shows the harmonic structure of the different
notes. Below is a spectrogram slice corresponding to the dotted line in the spectrogram view indicating the fundamental pitch and the associated harmonics according to the
nomenclature of Western music (F: fundamental; P8: perfect octave; P5: perfect fth; M2: major second; 3M: major third). Points over the dotted line indicate the fundamental
frequency (lowest point) and the associated harmonics in the spectrogram slice. Frequencies of the harmonics are exact integer multiples of the fundamental frequency.
M. Araya-Salas / Animal Behaviour 84 (2012) 309e313310
intervals, a particular type of musical interval formed by pairs of
notes related by small integer ratios. Similar integer ratios are
produced between a fundamental note and its harmonics and in
animal vocalizations. Hence, these scales represent the most intu-
itive pattern in which birds might base their songs.
Study Species and Sites
The nightingale wren is a resident of the understory of mature
forests from southern Mexico to northern Costa Rica (AOU 1998).
I recorded eight individuals from La Tirimbina Biological
Station (10
N; 84
W) with a Sony TCM-2000DV
recorder and a Sennheiser ME66 directional microphone. In addi-
tion, I obtained 73 recordings from bioacoustics archives from
eight sites (Supplementary Table S1). These recordingsbelong to nine
populations from the Caribbean Slope of Costa Rica and eight pop-
ulations from other locations in Central America and Mexico
(Supplementary Fig.S1). Thus, therecordings fairly represent the song
variation across the entire geographical distribution of the species.
I digitalized recordings from La Tirimbina at a sampling rate of
48 kHz. All other recordings were digitalized at a sampling rate of
44.1 kHz. I analysed the songs using Raven 1.2 software (Charif et al.
2004). For spectrogram analysis, I used the Hann window function,
a frame length of 202 samples, a lter bandwidth of 314 Hz, and the
Gray scalecolour scheme option. I measured the fundamental
frequency (the lowest frequency in a harmonic series) of each note.
Based on this variable I calculated the interval formed by adjacent
notes from the same song, dividing the fundamental frequency of
the second note of the interval by the fundamental frequency of the
rst note (Fig. 2). Thus, the intervals were expressed as ratios of
values between one and two. Ratios higher than two were divided
by integer multiples of two. This calculation allowed me to simplify
the analysis, keeping all the ratios in the same range without
changing the harmonic relation between notes (e.g. a ratio of 3 and
a ratio of 1.5 are harmonically the same: a perfect fth). Intervals
formed by repeated notes (notes with equal frequency; e.g. intro-
ductory notes) were omitted from the analysis. These notes create
harmonic intervals as a by-product of note repetition.
Data Analysis
For each bird, I tested the harmony of the entire number of
intervals (the intervals from all the songs). To carry out the analysis
Irst calculated for each frequency interval the distance to the
closest harmonic interval. The distance was considered as the
absolute difference between the observed interval ratio and the
closest harmonic interval ratio. For instance, two intervals with
values of 1.53 and 1.47 would have the same distance of 0.03 to the
closest harmonic interval (1.5; a perfect fth). In the harmonic
scales (described below), the range between harmonic intervals is
related to the magnitude of the intervals: the higher the magnitude
of the harmonic interval, the higher the range among subsequent
intervals. To account for this, I standardized the distance to the
closest harmonic interval by converting distances to percentages,
with 100% representing the closest distance (or an exact harmonic
interval) and 0% the furthest distance (exactly in the middle of two
harmonic intervals).
I used three musical scales derived from just intonationinter-
vals to test the conformity of the songs to harmonic intervals
(Fig. 3aec): chromatic scale (12 notes), major diatonic scale (seven
notes) and major pentatonic scale (ve notes). The chromatic scale
has the 12 intervals used in Western music, including consonant
and dissonant intervals (Fig. 3a). The other two scales (diatonic and
pentatonic) are subsets of the chromatic scale containing only the
intervals with the smallest integer ratios (called consonant inter-
vals). These intervals are formed by notes that share most of their
harmonics. The pentatonic scale contains the fundamental (or
octave), major second, major third, perfect fth and major sixth
(Fig. 3c), which are the intervals derived from the rst ve
harmonics. These are also the harmonics that are emphasized in the
nightingale wren whistles (Fig. 1). The diatonic scale contains,
additionally, the perfect fourth and major seventh (Fig. 3b), which
are derived from the sixth and seventh harmonics, respectively. The
chromatic scale also contains another type of interval created by
the secondary relationship between consonant intervals; these
intervals are called dissonant. For instance, if a tonic note is played,
followed by a major third, and then a major sixth is played from
that major third, the interval created by the last note and the tonic
note is a minor second, a dissonant interval. Hence the chromatic
scale would occur only if the notes have a harmonic relation to
notes two or more positions away in the song. Diatonic and
pentatonic scales would occur if the birds build harmonic intervals
only between immediately consecutive notes. Therefore, the scales
were selected under the criteria of assessing two levels of conso-
nance (pentatonic and diatonic scales) and evaluating the possible
harmonic relation among nonconsecutive notes (chromatic scale).
Although other subsets of intervals from the chromatic scale might
be formed, they would occlude some consonant intervals or mix
consonant and dissonant intervals with no clear criteria.
I used a null model to compare the observed intervals (repre-
sented by the percentage of the distance to the closest harmonic
interval) to expected nonharmonic values. Intervals from nonhar-
monic songs are expected to be uniformly distributed around
harmonic interval values. Hence, for each individual, I randomly
created a uniformly distributed variable of 10 000 values between
0 and 100. I then took 1000 subsets from the generated variable
Figure 2. Spectrogram of three notes of the nightingale wren showing the calculation
of interval ratios between adjacent notes. Dotted lines indicate the fundamental
frequency of the notes (frequency with the highest energy). Interval ratios were
dened as the ratio of the fundamental frequency of the second note to the rst note of
the interval.
Figure 3. Musical notation of three scales used to assess the conformity of the songs to
harmonic intervals: (a) chromatic scale (12 notes), (b) major diatonic scale (seven
notes) and (c) major pentatonic scale (ve notes). F: fundamental; m: minor; M: major;
P: perfect; A: augmented. Numbers represent the ordinal position of the note
(e.g. M2 ¼major second).
M. Araya-Salas / Animal Behaviour 84 (2012) 309e313 311
(with replacement), each one having a sample size equal to the
number of intervals of the individual to be compared. Each subset
was compared to the observed set of values with a Studentsttest.
The proportion of the 1000 tests in which the observed values were
not signicantly different from the uniform distribution was used
as the associated statistical probability. These analyses were carried
out in R version 2.9.0 (R Development Core Team 2009).
In addition, I analysed the melodies of musical compositions to
validate my method for detecting harmonic structure in acoustic
signals. I analysed songs from continuous pitch instruments. Unlike
instruments such as piano and ute, continuous pitch instruments
are not constrained to play notes at discrete intervals, allowing the
production of any possible interval in an octave, similar to an avian
syrinx and a human vocal tract. Hence, the intervals produced by
continuous pitch instruments represent an actual selection of
specic intervals by the musicians. Musical compositions were
obtained from commercial recordings or solo performances freely
available online (Supplementary Table S2). Compositions belong to
three musical styles: classical, jazz and popular music. A minimum
of 40 notes per song were included in the analysis. Intervals formed
by notes of equal frequency were discarded. Melodies were ana-
lysed in the same way as bird recordings.
Ethical Note
This research involved recording from nightingale wrens in the
wild. No birds were captured, and no behavioural experiments
were implemented. The study was conducted in compliance with
regulations of the Department of Environment and Energy of the
government of Costa Rica.
A total of 81 birds were used in the analysis. These birds
belonged to 16 song type populations: eight in Northern Costa Rica
and the rest from other sites across the speciesdistribution range
(see Supplementary Fig. S1). I carried out 243 comparisons (81 for
each of the three scales). A mean of 96 (range 15e970) intervals
were used in each test. Only ve birds (w6%) had intervals that
were signicantly closer to harmonic intervals than the expected
random distribution (2.5% of the 243 comparisons). In three cases
the intervals conformed to the pentatonic scale (MG8: P¼0.013;
TO5: P¼0.002; OC1: P¼0.037). One of these birds also conformed
to the diatonic scale (OC1 ¼0.044). Two other birds conformed to
00 20 40 60 80 100
Distance to the closest harmonic interval (%)
Harmonic interval
(a) (b) (c)
(d) (e) (f)
(g) (h) (i)
0 204060801000 20406080100
Harmonic interval Harmonic interval
Figure 4. Distance to harmonic intervals (chromatic scale) of adjacent note ratios from three nightingale wrens whose adjacent note ratios were nonsignicantly close to harmonic
intervals (aec, nonharmonic birds), three birds whose adjacent note ratios were signicantly close to harmonic intervals (def, harmonic birds) and three musical compositions
(gei). Distances are shown as percentages. In the histograms, 100% represents the closest distance (a perfect harmonic interval; thick lines) and 0% represents the furthest distance
(exactly in the middle of two harmonic intervals).
M. Araya-Salas / Animal Behaviour 84 (2012) 309e313312
the chromatic scale (LS8: P¼0.016; LS10: P¼0.032). Only two
birds belonged to the same population.
In contrast, my method successfully detected the harmonic
structure in musical compositions. From the 24 melodies analysed,
all were signicantly close to intervals from the chromatic scale
(P<0.003 in all cases), and 21 were also signicantly close to
intervals of both pentatonic and diatonic scales. Differences in the
distribution of frequency ratios in songs of nightingale wrens and
musical compositions are graphically shown in Fig. 4.
Nightingale wren songs are not organized by the same rules used
in musical composition. Overall, the frequency relation between
adjacent notes did not t with harmonic intervals, nor was thereany
consistency in the particular scale used in the few cases (2.5% of all
examined) where harmonic scales were detected. The few songs
that conformed to musical scales are probably an unintended
matching to harmony, which can be expected based on the large
sample size (81 birds, 243 comparisons). Given the uncommon use
of harmonic intervals in this species, my resultsstrongly suggest that
it is not an intentional feature of these birdsongs.
My method was successful in detecting harmonic intervals in
human musical compositions. All the melodies conformed to harmonic
intervals. My results, however, did not show a perfect match toall three
harmonic scales. The mismatch between some melodies and the
pentatonic and diatonic scales is most likely due to the use of intervals
not included in these scales but included in the chromatic scale.
Nightingale wren song is unusual among birdsongs in the extent
to which frequency alone, rather than duration or patterns of
frequency modulation, is the dominant difference among notes.
Thus, variation in note frequencies is the primary way to generate
song complexity (otherwise the song would be a series of equally
pitched whistles). This variation creates different note arrays,
which constitute the variation among song types (M. Araya-Salas,
T. F. Wright & G. Barrantes, unpublished data). If the harmonic
relationship between notes is not used as a rule to organize notes in
the song of this species, it seems even less likely that this occurs in
other birds with more complex song elements, in which song
variability seems to be emphasized in the production and combi-
nation of different types of elements (e.g. ascending or descending
whistles, broad-bandwidth elements, trills, etc.). Nevertheless, the
harmonic birdsong hypothesis remains to be tested in species with
more complex song elements.
This work represents the rst quantitative analysis for testing
whether the frequency shifts in a songbirds vocalizations conforms
to the harmonic intervals associated with human musicand provides
no support for a signicant role of harmonic intervals in the organi-
zation of the songs.This pattern might also occur in otherbird species
where versatility is not based on tonal variation between repeated
elements. The documented musical properties in other species may
be caused bya cultural bias of the human listenertowardsrecognizing
the occasional harmonic interval or by a simple misunderstanding of
the physicsof music composition, rather thanan actual characteristic
of the songs. This studyshould help bioacousticsresearchers to clarify
some notions about the acoustic structure of music and to recognize
the implicit assumptions when equating music and birdsong.
I thank Eduardo Chacon, Erick Fuchs, Federico Bolaños and
Gilbert Barrantes for stimulating discussion of ideas on early stages
of this manuscript, and Elizabeth Hobson, Timothy Wright, Johel
Chaves, Sean Ehlman and anonymous referees for comments on the
manuscript. I am also grateful to Borror Laboratory of Bioacoustics,
Bioacoustics Laboratory of Universidad de Costa Rica, Florida
Museum of Natural History, Macaulay Library, Alex Villegas, David
Bradley, Gerardo Obando and Julio Sanchez for access to recordings
and the Organization for Tropical Studies and Tirimbina Biological
Reserve for logistic support. Finally, I thank Evelyn Cubillo for help
and support during the development of this manuscript.
Supplementary Material
Supplementary material for this article is available, in the online
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... As another possibility, when cockatiels vocalize in unison, they may prefer the higher frequencies used for imitating whistle sounds to the lower frequencies used for imitating human speech. In any case, altogether, the present findings append further perspectives on the recent progress in comparative approaches for investigating human musicality [61][62][63][64][65][66]. ...
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It is known among aviculturists that cockatiels imitate human music with their whistle-like vocal sounds. The present study examined whether cockatiels are also able to sing “in unison”, or, line up their vocalizations with a musical melody so that they occur at the same time. Three hand-raised cockatiels were exposed to a musical melody of human whistling produced by an experimenter. All the birds learned to sing the melody. Then, two out of these three birds spontaneously joined in singing during an ongoing melody, so that the singing by the bird and the whistling by the human were nearly perfectly synchronous. Further experiments revealed that the birds actively adjusted their vocal timing to playback of a recording of the same melody. This means cockatiels have a remarkable ability for flexible vocal control similar to what is seen in human singing. The proximate/ultimate factors for this behavior and implications for musicality in humans are discussed.
... However, the degree of similarity and dif-40 ference between language, music, and animal song re-41 mains actively debated [14,32,20]. 42 While many studies have compared music with speech, hu-43 man song with bird song, or human speech with bird song 44 [1,14,19,32,41,42], there remain few quantitative at-45 tempts to characterize the degree of variation within and 46 between language, music, and birdsong using standardized 47 methods that can be objectively applied to all three do-48 mains. One such comparison found similarities in all three 49 domains for contour and interval size across a sample of 50 music from 5 countries, speech from 4 languages, and 51 songs from 56 bird species [42]. ...
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Scientists studying music and evolution often discuss similarities and differences between music, language, and bird song, but few studies have simultaneously compared these three domains quantitatively. To enable such com-parison, here we demonstrate several methods of cross-cultural/cross-species comparison of pitch structures in audio recordings. We utilized a small subset of 9 record-ings of human music, human speech, and bird song se-lected to maximize variation within and between these three domains. We extend previous automated analyses of scale structure and propose new methods for quantifying pitch discreteness and melodic interval structure, compar-ing automated analyses against human subjective ratings. Our quantitative analyses confirm that both human music and bird song can vary greatly along a continuum from pieces/songs with very discrete pitches and clear scale structure to those without. However, even the most “mu-sical” examples of speech showed minimal levels of dis-crete pitches or precise scales. On the other hand, all samples including human speech tended to use small in-tervals, consistent with the “motor constraint hypothesis”. Our analyses suggest that our methods can be used to ob-jectively perform meaningful cross-cultural and cross-species analysis of pitch structure from audio recordings, particularly after using our new pitch discreteness algo-rithm to screen and remove recordings that do not contain discrete pitches. We also identify areas in need of future development such as automated note segmentation and automated scale degree identification.
Some cockatiels are capable of imitating human music through song, and this ability is potentially a very interesting topic for researchers studying acoustic communication in animals. However, the vocalizations of this species, particularly their vocal sequences, have been mentioned very little in academic literature. This chapter reviews my own studies (including unpublished data) investigating the vocal behaviour of cockatiels, focusing on their capability for the imitation of human music and creative vocal production. Three hand-raised cockatiels in my laboratory were exposed to a melody of human music, which was performed through whistling. The birds produced vocal outputs in response to the melody before they had even fully fledged. Then, the birds spontaneously began to imitate the melody. The process by which the imitation developed varied among the birds. After they copied the melody, some of the birds spontaneously sang the melody in synchrony with a playback of the melody, much like humans do when they sing Happy Birthday together. Further, the cockatiels modified the patterns of the melody spontaneously. They also created some novel sound sequences without the presence of the model sounds. These findings provide insights into acoustic communication between conspecifics and heterospecifics. Given that we live in a world in which diverse creatures are living together, understanding others is of great importance.Keywords Parrots Rhythm Synchronization Creativity Drumming Percussion
Chapter 4 ended with the remark that the formation of an auditory unit can be strongly affected by sound components that precede and follow that auditory unit. This chapter describes the process in which successive auditory units are linked to each other to form auditory streams. An auditory stream is a sequence of auditory units that are perceived as coming from one and the same sound source. Examples are the successive syllables of a speech utterance, or the sequence of tones that together form a melody. The result of this complex process of auditory-stream formation is an auditory scene consisting of more or less well-defined auditory streams only one of which can be attended to effortlessly. Moreover, when the number of sound sources is more than three to four, listeners generally underestimate the number of sound sources in an auditory scene. The most important characteristic of an auditory stream is that the successive auditory units are temporally coherent, i.e., that they are well ordered in time and their beats form a well-defined rhythm. Establishing temporal coherence between successive auditory units is a complex process depending on many factors. These factors can be relatively simple, such as the pitch and the timbre of successive auditory units, or more complex factors such as the familiarity of the sounds. The result appears to be a very flexible and adaptive system that also operates well in very noisy circumstances such as bustling restaurants or cocktail parties. When segments of an auditory stream are masked by other sounds, the auditory system is highly capable of restoring this information in such a way that the listener is not aware of this restoration. Besides having a well-defined rhythm, auditory streams have well-defined loudness contours and, if at least the constituent auditory units have pitch, well-defined pitch contours, but these contours are not perceived independently of each other. In addition, the consonant and dissonant relations between the parallel streams of musical scenes are described. This chapter ends with the description of three different approaches to computational modelling of the auditory-stream-formation process.
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Das Anthropozän als gegenwärtiges Erdzeitalter ist (vgl. die sich seit dem Jahr 2000 vielfältig verzweigende diskursive Entwicklung in natur- wie in gesellschafts- und kulturwissenschaftlichen Disziplinen) von einer umfassenden Beeinflussung planetarer Entwicklungen durch Humanaktivitäten gekennzeichnet. Damit einher gehen beunruhigende und bedrohliche Begleiterscheinungen wie der Klimawandel, das Massenaussterben zahlreicher Arten, die Verschmutzung der Ozeane, aber auch das akustische Einwirken auf zahlreiche Tierarten durch menschengemachte Geräusche. Um Perspektiven einer weiteren Öffnung musiktheoretischer Fachlichkeit zur inter- und transdisziplinären Anthropozändiskussion zu eröffnen, werden zwei Vorschläge unterbreitet, mit welchen Methoden und anhand welcher Gegenstände Musiktheorien sich posthumanistisch weiterentwickeln könnten. Der erste Vorschlag ist, Musikkulturen nichtmenschlicher Tiere im Sinne des »Animal Turn« in musiktheoretischen Diskursen zu berücksichtigen. Vor allem dann, wenn Musiktheorie als empirisch exploratives Projekt des Verstehens und Systematisierens von musikalischer Praxis verstanden wird, bietet sich in den Gesängen und Instrumentallauten zahlreicher nichtmenschlicher Tiere ein reiches Untersuchungsfeld. Vorschlag zwei ist, die weitere Entwicklung künstlicher Kreativität musiktheoretisch zu begleiten. Insbesondere vor dem Hintergrund des Fortschritts im Bereich des Maschinellen Lernens ist das Potenzial für eine kreative Handlungsmacht (›Agency‹) von Künstlicher Intelligenz gegeben. Aus der Erweiterung der musiktheoretischen Perspektive, hin zur posthumanistisch informierten Berücksichtigung tierlicher und künstlicher Musikkreation, ergeben sich weitere Entwicklungsmöglichkeiten. Durch die Dekonstruktion anthropozentrischer Vorannahmen in der Musiktheorie und die Entwicklung von Theorien zu mehr-als-menschlichen Musiken kann Musiktheorie außerdem zusätzliche gesellschaftliche Relevanz erlangen.
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Birdsong is familiar but enigmatic: to some nothing but mechanical “instinct,” but so excessively exuberant that enthusiasts have linked the songs of birds to the development of the aesthetic sense. Where medieval scholars once saw the origins of music in the imitation of nature, by the Enlightenment birdsong was banished in the anthropocentric definition of art. In contrast to the philosophers, this paper focusses on human intervention in birdsong, focusing on the song of the domestic canary. The canary’s “contrived” song can be understood as a partnership between humans and birds, mediated by technology. Drawing on the European history of canary keeping, in Germany and Russia in particular, we turn first to the training of songbirds. Subsequently, we consider canaries as signature nonhuman performers, in spaces ranging from the home to the stage. Finally, we consider the role of technology, specifically recording and amplification, in making the canary’s song audible to audiences at a distance. The salutary hybridization of animal–human-machine contests the longstanding condescension of philosophers towards mechanical artifice and any contamination of the free beauties of nature.
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Bird songs often display musical acoustic features such as tonal pitch selection, rhythmicity, and melodic contouring. We investigated higher-order musical temporal structure in bird song using an experimental method called “music scrambling” with human subjects. Recorded songs from a phylogenetically diverse group of 20 avian taxa were split into constituent elements (“notes” or “syllables”) and recombined in original and random order. Human subjects were asked to evaluate which version sounded more “musical” on a per-species basis. Species identity and stimulus treatment were concealed from subjects, and stimulus presentation order was randomized within and between taxa. Two recordings of human music were included as a control for attentiveness. Participants varied in their assessments of individual species musicality, but overall they were significantly more likely to rate bird songs with original temporal sequence as more musical than those with randomized temporal sequence. We discuss alternative hypotheses for the origins of avian musicality, including honest signaling, perceptual bias, and arbitrary aesthetic coevolution.
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Musical improvisation and biological evolution are similarly based on the principles of unpredictability and adaptivity. Against this background, this research examines whether and how structures of evolutionary developmental logic can be detected and described in free improvisation. The underlying con- cept of improvisation is participative in nature and, in this reading, contains similar generative strategies as there are in evolutionary processes. Further im- plications of the theory of evolution for cultural development – as the concept of memetics – and for computer science – in the form of genetic algorithms – build an interdisciplinary network of different theories and methodologies, from which the proposed model of genetic improvisation emerges. An improvisation thereby arises as an evolution of individual sound cells with a specific sound repertoire as their phenotype. The meta-generative function of the sound cell thus combines the analytical with the generative, in that its genotype codes for improvisational phylogenesis at the same time define its sounding ontogenesis. If this principle is reversed and – in the sense of reverse engineering – app- lied to a corpus of recorded improvisations with methods of bioinformatics for empirical analysis, a co-adaptive network of lineages of sound cells can be created. This structured approach allows not only a systematic analysis by means of gene pools but also a hermeneutic interpretation of the material along the visualisations in phylogenetic trees. It turns out that, after the individual-creative selection of sound cells, the second level of interactive se- lection between the improvisers becomes effective, which on the genetic level appears complementary to the dominant principle of imitation. To evaluate the epistemological status of these results, however, it is always necessary to read them in the context of their hybrid genesis between subjectivity and digitality.
In the current resurgence of interest in the biological basis of animal behavior and social organization, the ideas and questions pursued by Charles Darwin remain fresh and insightful. This is especially true of The Descent of Man and Selection in Relation to Sex, Darwin's second most important work. This edition is a facsimile reprint of the first printing of the first edition (1871), not previously available in paperback. The work is divided into two parts. Part One marshals behavioral and morphological evidence to argue that humans evolved from other animals. Darwin shoes that human mental and emotional capacities, far from making human beings unique, are evidence of an animal origin and evolutionary development. Part Two is an extended discussion of the differences between the sexes of many species and how they arose as a result of selection. Here Darwin lays the foundation for much contemporary research by arguing that many characteristics of animals have evolved not in response to the selective pressures exerted by their physical and biological environment, but rather to confer an advantage in sexual competition. These two themes are drawn together in two final chapters on the role of sexual selection in humans. In their Introduction, Professors Bonner and May discuss the place of The Descent in its own time and relation to current work in biology and other disciplines.
From two to five frequency peaks, representing sustained portions of white‐throated sparrow (Z o n o t r i c h i a a l b i c o l l i s) song, were derived using a Ubiquitous Spectrum Analyzer for each of more than 300 recorded songs from 58 different birds. After conversion to cents, a logarithmic unit, each bird’s song data were averaged and placed into three distributions: largest interval in whole song, largest interval between adjacent notes in each song, and all intervals between adjacent frequency peaks in each song. These three distributions plus another from African shrike data previously published by Thorpe did not significantly correlate with a distribution derived from commonly used Western musical scales. It is therefore suggested that utilization of Western musical notation may lead one to overemphasize the ’’musical’’ quality of bird song.
Author Institution: Department of Zoology and Entomology, The Ohio State University, Columbus 10