Natural soundscapes correspond to the acoustical patterns produced by biological and geophysical sound sources at different spatial and temporal scales for a given habitat. This pilot study aims to characterize the temporal-modulation information available to humans when perceiving variations in soundscapes within and across natural habitats. This is addressed by processing soundscapes from a previous study [Krause, Gage, and Joo. (2011). Landscape Ecol. 26, 1247] via models of human auditory processing extracting modulation at the output of cochlear filters. The soundscapes represent combinations of elevation, animal, and vegetation diversity in four habitats of the biosphere reserve in the Sequoia National Park (Sierra Nevada, USA). Bayesian statistical analysis and support vector machine classifiers indicate that: (i) amplitude-modulation (AM) and frequency-modulation (FM) spectra distinguish the soundscapes associated with each habitat; and (ii) for each habitat, diurnal and seasonal variations are associated with salient changes in AM and FM cues at rates between about 1 and 100 Hz in the low (<0.5 kHz) and high (>1–3 kHz) audio-frequency range. Support vector machine classifications further indicate that soundscape variations can be classified accurately based on these perceptually inspired representations.

1.
Acevedo
,
M. A.
, and
Villanueva-Rivera
,
L. J.
(
2006
). “
Using automated digital recording systems as effective tools for the monitoring of birds and amphibians
,”
Wildlife Soc. Bull.
34
,
211
214
.
3.
Bacon
,
S. P.
, and
Grantham
,
D. W.
(
1989
). “
Modulation masking patterns: Effects of modulation frequency, depth and phase
,”
J. Acoust. Soc. Am.
85
,
2575
2580
.
4.
Bosker
,
H. R.
, and
Cooke
,
M.
(
2018
). “
Talkers produce more pronounced amplitude modulations when speaking in noise
,”
J. Acoust. Soc. Am.
143
,
EL121
EL126
.
5.
Brumm
,
H.
(
2013
).
Animal Communication and Noise (Animal Signals and Communication)
(
Springer
,
Berlin
), Vol.
2
.
6.
Brumm
,
H.
, and
Zollinger
,
S. A.
(
2013
). “
Avian vocal production in noise
,” in
Animal Communication and Noise, Animal Signals and Communication
, edited by
H.
Brumm
(
Springer
,
Berlin
), Vol.
2
, pp.
187
228
.
8.
Dau
,
T.
,
Kollmeier
,
D.
, and
Kohlrausch
,
A.
(
1997
). “
Modeling auditory processing of amplitude modulation: I. Detection and masking with narrowband carriers
,”
J. Acoust. Soc. Am.
102
,
2892
2905
.
9.
Drullman
,
R.
(
1995
). “
Temporal envelope and fine structure cues for speech intelligibility
,”
J. Acoust. Soc. Am.
97
,
585
592
.
10.
Ewert
,
S. D.
, and
Dau
,
T.
(
2000
). “
Characterizing frequency selectivity for envelope fluctuations
,”
J. Acoust. Soc. Am.
108
,
1181
1196
.
11.
Ey
,
E.
, and
Fischer
,
J.
(
2009
). “
The ‘acoustic adaptation hypothesis’—A review of the evidence from birds, anurans and mammals
,”
Bioacoustics
19
,
21
48
.
12.
Farina
,
A.
(
2014
).
Soundscape Ecology: Principles, Patterns, Methods and Applications
(
Springer
,
New York
).
13.
Farina
,
A.
, and
Gage
,
S. H.
(
2017
).
Ecoacoustics: The Ecological Role of Sounds
(
Wiley
,
New York
).
14.
Fay
,
R.
(
2009
). “
Soundscapes and the sense of hearing of fishes
,”
Integr. Zool.
4
(
1
),
26
32
.
15.
Fu
,
Q. J.
(
2002
). “
Temporal processing and speech recognition in cochlear implant users
,”
Neuroreport
13
,
1635
1639
.
16.
Gage
,
S. H.
, and
Farina
,
A.
(
2017
). “
Ecoacoustics challenges
,” in
Ecoacoustics: The Ecological Role of Sounds
(
Wiley
,
New York
), pp.
313
319
.
17.
Gasc
,
A.
,
Francomano
,
D.
,
Dunning
,
J. B.
, and
Pijanowski
,
B. C.
(
2016
). “
Future directions for soundscape ecology: The importance of ornithological contributions
,”
The Auk
134
,
215
228
.
18.
Glasberg
,
B. R.
, and
Moore
,
B. C.
(
1990
). “
Derivation of auditory filter shapes from notched-noise data
,”
Hear. Res.
47
,
103
138
.
19.
Gygi
,
B.
,
Kidd
,
G. R.
, and
Watson
,
C. S.
(
2004
). “
Spectro temporal factors in the identification of environmental sounds
,”
J. Acoust. Soc. Am.
115
,
1252
1265
.
20.
Hilbert
,
D.
(
1912
).
Grundzüge einer allgemeinen theorie der linearen integralgleichungen (Fundamentals of a General Theory of Linear Integral Equations)
University of California Libraries (
Teubner
,
Leipzig
).
21.
Houtgast
,
T.
(
1989
). “
Frequency selectivity in amplitude-modulation detection
,”
J. Acoust. Soc. Am.
85
,
1676
1680
.
23.
Hsu
,
A.
,
Woolley
,
S. M. N.
,
Fremouw
,
T. E.
, and
Theunissen
,
F. E.
(
2004
). “
Modulation power and phase spectrum of natural sounds enhance neural encoding performed by single auditory neurons
,”
J. Neurosci.
24
,
9201
9211
.
24.
Huang
,
N.
, and
Elhilali
,
M.
(
2017
). “
Auditory salience using natural soundscapes
,”
J. Acoust. Soc. Am.
141
,
2163
2176
.
25.
Johannesen
,
P. T.
,
Pérez-González
,
P.
,
Kalluri
,
S.
,
Blanco
,
J. L.
, and
Lopez-Poveda
,
E. A.
(
2016
). “
The influence of cochlear mechanical dysfunction, temporal processing deficits, and age on the intelligibility of audible speech in noise for hearing-impaired listeners
,”
Trends Hear.
20
,
2331216516641055
.
26.
Joris
,
P. X.
,
Schreiner
,
C. E.
, and
Rees
,
A.
(
2004
). “
Neural processing of amplitude-modulated sounds
,”
Physiol. Rev.
84
,
541
577
.
27.
Kates
,
J. M.
, and
Arehart
,
K. H.
(
2014
). “
The Hearing-Aid Speech Perception Index (HASPI)
,”
Speech Commun.
65
,
75
93
.
28.
King
,
A.
,
Varnet
,
L.
, and
Lorenzi
,
C.
(
2019
). “
Accounting for the masking of frequency modulation by amplitude modulation using the modulation-filterbank concept
,”
J. Acoust. Soc. Am.
145
,
2277
2293
.
30.
Koumura
,
T.
,
Terashima
,
H.
, and
Furukawa
,
S.
(
2019
). “
Cascaded tuning to amplitude modulation for natural sound recognition
,”
J. Neurosci.
10
,
5517
5533
.
31.
Krause
,
B.
(
1987
). “
Bioacoustics, habitat ambience in ecological balance
,”
Whole Earth Rev.
57
,
14
18
.
32.
Krause
,
B.
(
2016
).
Wild Soundscapes: Discovering the Voice of the Natural World
(
Yale University Press
,
New Haven, CT
).
33.
Krause
,
B.
, and
Farina
,
A.
(
2016
). “
Using ecoacoustic methods to survey the impacts of climate change on biodiversity
,”
Biol. Conserv.
195
,
245
254
.
34.
Krause
,
B.
,
Gage
,
S. H.
, and
Joo
,
W.
(
2011
). “
Measuring and interpreting the temporal variability in the soundscape at four places in Sequoia National Park
,”
Landscape Ecol.
26
,
1247
1256
.
36.
Kruschke
,
J. B.
(
2010
).
Doing Bayesian Data Analysis: A Tutorial with R and BUGS
(
Academic
,
Orlando
).
37.
McDermott
,
J. H.
, and
Simoncelli
,
E. P.
(
2011
). “
Sound texture perception via statistics of the auditory periphery: Evidence from sound synthesis
,”
Neuron
71
,
926
940
.
38.
McWalter
,
R.
, and
Dau
,
T.
(
2017
). “
Cascaded amplitude modulations in sound texture perception
,”
Front. Neurosci.
11
,
485
.
39.
McWalter
,
R.
, and
McDermott
,
J. H.
(
2018
). “
Adaptive and selective time averaging of auditory scenes
,”
Curr. Biol.
28
,
1405
1418
.
40.
Moore
,
B. C. J.
(
2008
). “
The role of temporal fine structure processing in pitch perception, masking, and speech perception for normal-hearing and hearing-impaired people
,”
J. Assoc. Res. Otolaryngol.
9
,
399
406
.
41.
Moore
,
B. C. J.
,
Glasberg
,
B. R.
, and
Baer
,
T.
(
1997
). “
A model for the prediction of thresholds, loudness and partial loudness
,”
J. Audio Eng. Soc.
45
,
224
240
.
42.
Moore
,
B. C. J.
, and
Sek
,
A.
(
1996
). “
Detection of frequency modulation at low modulation rates: Evidence for a mechanism based on phase locking
,”
J. Acoust. Soc. Am.
100
,
2320
2331
.
43.
Morton
,
E. S.
(
1975
). “
Ecological sources of selection on avian sounds
,”
Am. Nat.
109
,
17
34
.
44.
Paraouty
,
N.
,
Ewert
,
S.
,
Wallaert
,
N.
, and
Lorenzi
,
C.
(
2016
). “
Interactions between amplitude modulation and frequency modulation processing: Effects of age and hearing loss
,”
J. Acoust. Soc. Am.
140
,
121
131
.
45.
Paraouty
,
N.
,
Stasiak
,
A.
,
Lorenzi
,
C.
,
Varnet
,
L.
, and
Winter
,
I. M.
(
2018
). “
Dual coding of frequency modulation in the ventral cochlear nucleus
,”
J. Neurosci.
38
,
4123
4137
.
46.
Parthasarathy
,
A.
,
Hancock
,
K. E.
,
Bennett
,
K.
,
DeGruttola
,
V.
, and
Polley
,
D. B.
(
2020
). “
Bottom-up and top-down neural signatures of disordered multi-talker speech perception in adults with normal hearing
,”
Elife.
21
,
e51419
.
47.
Patterson
,
R. D.
,
Allerhand
,
M. H.
, and
Giguere
,
C.
(
1995
). “
Time-domain modeling of peripheral auditory processing: A modular architecture and a software platform
,”
J. Acoust. Acoust. Am.
98
,
1890
1894
.
48.
Pedregosa
,
F.
,
Varoquaux
,
G.
,
Gramfort
,
A.
,
Michel
,
V.
,
Thirion
,
B.
,
Grisel
,
O.
,
Blondel
,
M.
,
Prettenhofer
,
P.
,
Weiss
,
R.
,
Dubourg
,
V.
,
Vanderplas
,
J.
,
Passos
,
A.
,
Cournapeau
,
D.
,
Brucher
,
M.
,
Perrot
,
M.
, and
Duchesnay
,
E.
(
2011
). “
Scikit-learn: Machine learning in Python
,”
J. Mach. Learn. Res.
12
,
2825
2830
.
49.
Pijanowski
,
B. C.
,
Villanueva-Rivera
,
L. J.
,
Dumyahn
,
S. L.
,
Farina
,
A.
,
Krause
,
B. L.
,
Napoletano
,
B. M.
,
Gage
,
S. H.
, and
Pieretti
,
N.
(
2011
). “
Soundscape ecology: The science of sound in the landscape
,”
Bioscience
61
,
203
216
.
50.
Plomp
,
R.
(
1983
). “
Perception of speech as a modulated signal
,” in
Proceedings of the 10th International Congress of Phonetic Sciences
, Utrecht, pp.
19
40
.
51.
Plomp
,
R.
(
1988
). “
The negative effect of amplitude compression in multichannel hearing aids in the light of the modulation-transfer function
,”
J. Acoust. Soc. Am.
83
,
2322
2327
.
52.
Plummer
,
M.
(
2003
). “
JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling
,” in
Proceedings of the 3rd International Workshop on Distributed Statistical Computing
, Vienna, Austria.
53.
Press
,
W. H.
,
Flannery
,
B. P.
,
Teukolsky
,
S. A.
, and
Vetterling
,
W. T.
(
1992
).
Numerical Recipes in Fortran 77: The Art of Scientific Computing
, 2nd ed. (
Cambridge University Press
,
Cambridge, UK
).
54.
Rees
,
A.
, and
Kay
,
R. H.
(
1985
). “
Delineation of FM rate channels in man by detectability of a three-component modulation waveform
,”
Hear. Res.
18
,
211
221
.
55.
Rees
,
A.
, and
Malmierca
,
M. S.
(
2005
). “
Processing of dynamic spectral properties of sounds
,”
Int. Rev. Neurobio.
70
,
299
330
.
56.
Rodriguez
,
F. A.
,
Chen
,
C.
,
Read
,
H. L.
, and
Escabi
,
M. A.
(
2010
). “
Neural modulation tuning characteristics scale to efficiently encode natural sound statistics
,”
J. Neurosci.
30
,
15969
15980
.
57.
Römer
,
H.
(
2013
). “
Masking by noise in acoustic insects: Problems and solutions,” in Animal Communication and Noise
,
Animal Signals and Communication
, edited by
H.
Brumm
(
Springer
,
Berlin
), Vol.
2
, pp.
3
64
.
58.
Rosen
,
S.
(
1992
). “
Temporal information in speech: Acoustic, auditory and linguistic aspects
,”
Philos. Trans. R. Soc. Lond. B. Biol. Sci.
336
,
367
373
.
59.
Saberi
,
K.
, and
Hafter
,
E. R.
(
1995
). “
A common neural code for frequency- and amplitude-modulated sounds
,”
Nature
374
,
537
539
.
60.
Schafer
,
R. M.
(
1977
).
Tuning of the World
(
Knopf
,
New York
).
61.
Schwartz
,
J. J.
, and
Bee
,
M. A.
(
2013
). “
Anuran acoustic signal production in noisy environments
,”
Animal Communication and Noise, Animal Signals and Communication
, edited by
H.
Brumm
(
Springer
,
Berlin
), Vol.
2
, pp.
91
132
.
62.
Shafiro
,
V.
(
2008
). “
Identification of environmental sounds with varying spectral resolution
,”
Ear Hear.
29
,
401
420
.
63.
Shamma
,
S.
, and
Lorenzi
,
C.
(
2013
). “
On the balance of envelope and temporal fine structure in the encoding of speech in the early auditory system
,”
J. Acoust. Soc. Am.
133
,
2818
2833
.
64.
Shannon
,
R. V.
,
Zeng
,
F. G.
,
Kamath
,
V.
,
Wygonski
,
J.
, and
Ekelid
,
M.
(
1995
). “
Speech recognition with primarily temporal cues
,”
Science
270
,
303
304
.
66.
Singh
,
N. C.
, and
Theunissen
,
F. E.
(
2003
). “
Modulation spectra of natural sounds and ethological theories of auditory processing
,”
J. Acoust. Soc. Am.
114
,
3394
3411
.
67.
Steeneken
,
H. J. M.
, and
Houtgast
,
T.
(
1980
). “
A physical method for measuring speech-transmission quality
,”
J. Acoust. Soc. Am.
67
,
318
326
.
70.
Sueur
,
J.
, and
Farina
,
A.
(
2015
). “
Ecoacoustics: The ecological investigation and interpretation of environmental sound
,”
Biosemiotics
8
,
493
502
.
71.
Sueur
,
J.
,
Farina
,
A.
,
Gasc
,
A.
,
Pieretti
,
N.
, and
Pavoine
,
S.
(
2014
). “
Acoustic indices for biodiversity assessment and landscape investigation
,”
Acta Acust. Acust.
100
,
772
781
.
72.
Sueur
,
J.
,
Pavoine
,
S.
,
Hamerlynck
,
O.
, and
Duvail
,
S.
(
2008
). “
Rapid acoustic survey for biodiversity appraisal
,”
PLoS One
3
,
e4065
.
74.
Truax
,
B.
(
1999
).
Handbook of Acoustic Ecology
, 2nd ed. (CD-ROM) (
Cambridge Street
,
Burnaby, BC
).
75.
Ulloa
,
J. S.
,
Aubin
,
T.
,
Llusia
,
D.
,
Bouveyron
,
C.
, and
Sueur
,
J.
(
2018
). “
Estimating animal acoustic diversity in tropical environments using unsupervised multiresolution analysis
,”
Ecol. Indic.
90
,
346
355
.
76.
Varnet
,
L.
,
Ortiz-Barajas
,
M. C.
,
Erra
,
R. G.
,
Gervain
,
J.
, and
Lorenzi
,
C.
(
2017
). “
A cross-linguistic study of speech modulation spectra
,”
J. Acoust. Soc. Am.
142
,
1976
1989
.
79.
Zeng
,
F.-G.
,
Nie
,
K.
,
Stickney
,
G. S.
,
Kong
,
Y.-Y.
,
Vongphoe
,
M.
,
Bhargave
,
A.
,
Wei
,
C.
, and
Cao
,
K.
(
2005
). “
Speech recognition with amplitude and frequency modulations
,”
Proc. Natl. Acad. Sci. U.S.A.
102
,
2293
2298
.

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