Access to this full-text is provided by Frontiers.
Content available from Frontiers in Psychology
This content is subject to copyright.
REVIEW ARTICLE
published: 13 January 2015
doi: 10.3389/fpsyg.2014.01543
Revisiting vocal perception in non-human animals: a review
of vowel discrimination, speaker voice recognition, and
speaker normalization
Buddhamas Kriengwatana1,2*, Paola Escudero3and Carel ten Cate1,2
1Behavioural Biology, Institute for Biology Leiden, Leiden University, Leiden, Netherlands
2Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
3The MARCS Institute, University of Western Sydney, Sydney, NSW, Australia
Edited by:
Janet F. Werker, The University of
British Columbia, Canada
Reviewed by:
LouAnn Gerken, University of Arizona,
USA
Andrew J. Lotto, University of
Arizona, USA
Marilyn Vihman, University of York, UK
*Correspondence:
Buddhamas Kriengwatana,
Behavioural Biology, Institute for
Biology Leiden, Leiden University,
Sylviusweg 72, Leiden 2333BE,
Netherlands
e-mail: bkrieng@alumni.uwo.ca
The extent to which human speech perception evolved by taking advantage of predis-
positions and pre-existing features of vertebrate auditory and cognitive systems remains
a central question in the evolution of speech. This paper reviews asymmetries in vowel
perception, speaker voice recognition, and speaker normalization in non-human animals –
topics that have not been thoroughly discussed in relation to the abilities of non-human
animals, but are nonetheless important aspects of vocal perception. Throughout this
paper we demonstrate that addressing these issues in non-human animals is relevant and
worthwhile because many non-human animals must deal with similar issues in their natural
environment. That is, they must also discriminate between similar-sounding vocalizations,
determine signaler identity from vocalizations, and resolve signaler-dependent variation
in vocalizations from conspecifics. Overall, we find that, although plausible, the current
evidence is insufficiently strong to conclude that directional asymmetries in vowel
perception are specific to humans, or that non-human animals can use voice characteristics
to recognize human individuals. However, we do find some indication that non-human
animals can normalize speaker differences. Accordingly, we identify avenues for future
research that would greatly improve and advance our understanding of these topics.
Keywords: asymmetries in vowel perception, comparative cognition, general auditory approach, voice perception,
language evolution, animal behavior, speaker normalization
INTRODUCTION
The answer to how humans perceive speech has eluded researchers
for over half a century (Jusczyk and Luce, 2002;Samuel, 2011).
Remarkably, studies in non-human animals (hereafter referred to
as animals) have shown that animals can also solve certain prob-
lems that are crucial to human speech perception, such as lack
of invariance and compensation for co-articulation (e.g., Kluen-
der et al., 1987;Lotto et al., 1997a). The results of these pioneering
studies have shown remarkable similarities, but also differences,in
perception, discrimination, and sensitivity to acoustic properties
of speech in humans and animals (reviewed by Kuhl, 1981;Lotto
et al., 1997b;Kluender et al., 2005;Beckers, 2011;Carbonell and
Lotto, 2014;ten Cate, 2014). Consequently,many researchers have
adopted the general auditory approach outlined by Diehl et al.
(2004), which is a framework for the idea that human speech per-
ception is achieved via general learning mechanisms and auditory
principles common to humans and animals.
From a general auditory approach, categorical perception
occurs at natural psychophysical boundaries constrained by the
functioning of the auditory system (Kuhl and Miller, 1975), com-
pensation for coarticulation is possible by contrasting spectral
patterns of high and low energy in particular frequency regions
(Lotto et al., 1997b;Diehl et al., 2004), and the lack of invariance in
speech can be solved in ways similar to concept formation for visual
categories that cannot be defined by any single cue (Kluender et al.,
1987). Furthermore, phonetic category learning by humans and
animals can potentially be achieved via statistical learning and per-
ceptual learning mechanisms. Statistical learning can account for
how human infants (Maye et al., 2002), but also rats (Pons, 2006),
use the distributional properties of acoustic input to learn phonetic
categories, such that exposure to a speech sound continuum with
unimodal or bimodal distribution can result in acquisition of one
or two phonetic categories, respectively. Statistical learning also
appears to underlie our ability to use recurring sound sequences
in speech to denote word boundaries (Saffran et al., 1996;Peluc-
chi et al., 2009), which is also observed when stimuli are tones or
musical sounds (Saffran et al., 1999;Gebhart et al., 2009). Thus,
statistical learning is a general learning mechanism that is not spe-
cific to speech, but is useful for speech perception because it can
be used to map acoustic properties onto phonetic categories in a
probabilistic manner (Holt et al., 1998).
Altogether, these studies culminate to form the current dom-
inant view that at least several processes involved in speech
perception in humans can be traced back to predispositions, learn-
ing mechanisms and rudimentary features of vertebrate cognitive
and auditory systems also present in other species (e.g., Car-
bonell and Lotto, 2014). Nevertheless, an enduring and central
question in the evolution of speech and language is whether
our extraordinary abilities to deal with the enormous variety
of speech sound and voices is a matter of degree compared to
www.frontiersin.org January 2015 |Volume 5 |Article 1543 |1
Kriengwatana et al. Revisiting vocal perception in animals
the abilities of animals, or the result of an evolutionary quan-
tum leap resulting in novel and unique specialized mechanisms.
Animals have, of course, never been under selection to process
speech sounds or recognize voices. If they would also process
their own communication sounds similar to how humans do,
this might indicate a more general mechanism, but might also
indicate an independently evolved perceptual mechanism highly
specific to their own vocal communication. Hence, a much
stronger indication for the presence of general perceptual mecha-
nisms would be if animals process human speech sounds similar
to humans. This would indicate that our ability to handle the
complexities of speech likely arose from an amalgamation and
adaptation of simpler mechanisms present in other vocalizing
animals. Comparative studies can thus provide an invaluable
window into the uniqueness and origin of speech processing
mechanisms.
The objective of this paper is to extend the discussion of
species-shared perceptual mechanisms to aspects of human speech
perception and voice recognition that have not been consid-
ered central to conventional theories of speech perception, but
nonetheless cannot be ignored. Specifically, we focus our review on
asymmetries in vowel perception, speaker voice recognition, and
speaker normalization and underline how these areas of research
can benefit from incorporating comparative perspectives. Review-
ing these topics contributes significantly to the debate about the
nature and specialness (or generality) of human speech percep-
tion because asymmetries in vowel perception may play a crucial
role in the development of infant speech perception (Polka and
Bohn, 2011), voice perception impacts speech perception (e.g.,
Nygaard and Pisoni, 1998), and intrinsic speaker normalization
is just as meaningful an issue as extrinsic speaker normaliza-
tion because both are concerned with the problem of perceptual
invariance in vowel perception (e.g., Johnson, 2005). Thus, our
manuscript provides the first detailed review necessary for a more
thorough understanding of whether the mechanisms that mediate
asymmetries in vowel perception, voice recognition, and speaker
normalization in humans arose from an evolutionary quantum
leap, or from tuning and remodeling of existing mechanisms
that are also present in non-human species (whether by common
descent or by independent evolution unconnected to the presence
of speech).
ASYMMETRIES IN VOWEL PERCEPTION
Polka and Bohn (2003,2011) review numerous studies on vowel
discrimination in human infants and adults. These studies demon-
strate a striking directional asymmetry: discrimination of native
or non-native vowels by infants and of non-native vowels by adults
is easier when the change is from a vowel occupying a more cen-
tral position in the F1/F2 vowel space to a vowel occupying a more
peripheral position (e.g., from /e/ to /i/).Of the dozens of studies
reviewed, only one showed that a change from a more to a less
peripheral vowel was easier to discriminate than a change in the
reverse direction (Best and Faber, 2000 as cited in Polka and Bohn,
2003,2011), and this was attributed to effects of vowel rounding
in F3. Polka and Bohn (2003,2011) assert that this directional
asymmetry helps infants to acquire phonetic categories because
the most peripheral vowels /i/, /a/, and /u/ found in all human
languages act as stable referents from which infants can perceptu-
ally organize their vowel space (see, Polka and Bohn, 2011 for these
ideas in the context of the natural referent vowel framework). The
authors propose that these biases are specific to humans due to
their role in organizing the vowel space and presence very early in
development. Emphatically, Polka and Bohn (2003,2011) claim
that these directional asymmetries do not reflect a general audi-
tory processing bias and therefore will not be present in other
animals.
To support their claim of species-specificity in the asymme-
tries observed in human vowel perception, Polka and Bohn (2003)
examined vowel discrimination data from red-winged blackbirds
(Agelaius phoeniceus), pigeons (Columba livia), and cats (Hienz
et al., 1981,1996). While red-winged blackbirds and cats (but not
pigeons) also exhibited asymmetries in vowel perception, discrim-
ination was almost always easier when formant frequencies were
shifted upward (e.g., from /O/to/A/orfrom/U/ to /æ/).
These results, however, do not resolutely show that the cen-
tral to peripheral bias found in humans is uniquely human. This
is because these experiments do not test discrimination between
more and less peripheral vowels. Hienz et al. (1981) tested dis-
crimination of the peripheral vowels /O/, /A/, /æ/, /E/, which does
not test whether animals find the change from a central vowel
to a peripheral vowel easier to discriminate. Hienz et al. (1996)
tested discrimination between the slightly more central vowel /U/
and the peripheral vowels /A/, /æ/, and /E/, and found that the
change from /U/to/A/, /U/ to /æ/, and //U/to/E/ was easier to
discriminate than the change in the opposite direction (e.g., /A/to
/U/). Therefore, these results in fact suggest that animals also find
the change from a central vowel to peripheral vowel easier to dis-
criminate. Nevertheless, differences in discrimination by humans
and non-human animals on the same speech contrasts are cer-
tainly needed to conclude that the asymmetry patterns observed
in humans are truly unique to humans. The only contrast that was
tested in both humans and red-winged blackbirds was the /E/-/æ/
contrast. In this case, 6–8 and 10–12 month-old human infants
found the discrimination easier if the change occurred from /E/
to /æ/, whereas birds found the change in the reverse direction
easier to discriminate (Hienz et al., 1981;Polka and Bohn, 1996).
This directional asymmetry was recently found in even younger
infants (2–3 month-olds) that were exposed to /E/ and /æ/ vowels
that were bimodally distributed along an [E-æ] continuum (Wan-
rooij et al., 2014), and was treated as further evidence to support
the central to peripheral bias in humans (Bohn and Polka, 2014).
However, as both /E/ and /æ/ occupy peripheral positions in vowel
space, this asymmetry can only falsify the central to peripheral
bias if we assume that the change from /E/ to /æ/ is easier to dis-
criminate because /æ/ is closer to the vowel referent /a/ than /E/is
to the vowel referent /i/ – according to the natural vowel referent
framework, /a/, /i/, and /u/ are vowel referents because they are
the most peripheral vowels (Polka and Bohn, 2011). Whether this
assumption is correct is not explicitly stated in Polka and Bohn
(2003,2011), but if it is then it is the only vowel contrast so far that
could be argued to reflect a human-specific vowel discrimination
bias.
Missing from Polka and Bohn’s (2003,2011) reviews was work
by Sinnott (1989), who compared detection and discrimination of
Frontiers in Psychology |Language Sciences January 2015 |Volume 5 |Article 1543 |2
Kriengwatana et al. Revisiting vocal perception in animals
synthetic English vowels by human adults and monkeys (vervets
Cercopithecus aethiops and Japanese macaque Macaca fuscata).
Subjects had to discriminate between two sets of vowels: /i-I-E-
æ-Ç-2-A/ (mostly front vowels with higher F2) and /2-A-O-U-u/
(mostly back vowels with lower F2). Sinnott (1989) used a repeat-
ing standard XA task, where subjects pressed a lever to hear a
repeating standard vowel followed by two repetitions of a com-
parison vowel. Subjects had to release the lever if they perceived
the comparison vowel to be different from the standard vowel.
Every vowel in each of the two sets served as both standard and
comparison vowels. We used these data to assess the asymmetries
in monkey vowel discrimination (Sinnott, 1989, Table II, p. 560).
These directional asymmetries are portrayed visually in Figure 1.
We only considered directional asymmetries to be present when
the difference between the percent of time a vowel comparison was
missed following a particular standard was greater than 25. For
example, the /u-U/ asymmetry for vervets was included because
vervets missed the change from /u/ to /U/ 93 percent of the time,
but missed the change from /U/ to /u/ only 2% of the time.
Figure 1 shows that, for back vowels, vervets perform simi-
larly to red-winged blackbirds and cats (Hienz et al., 1981,1996).
That is, their discrimination of back vowels is enhanced if the
F1 and F2 of the comparison vowel are increased relative to the
standard vowel. However, vervets and macaques (but not adult
humans) most likely perceive decreases in F2 of these vowels as
decreases in intensity (Sinnott, 1989), and earlier work by Sin-
nott et al. (1985) showed that vervets and macaques have difficulty
detecting decrements in intensity. That is, humans, macaques, and
vervets required similar intensities to be able to detect front vow-
els, but monkeys required back vowels to be presented ∼10–20 dB
louder than humans to be able to detect them (Sinnott, 1989).
Examination of F1, F2, and F3 values of the vowel stimuli showed
that monkeys’ detection thresholds were correlated with decreases
in F2. This suggested that monkeys required higher intensities
in order to be able to detect vowels that decrease in F2 (Sinnott,
FIGURE 1 |Plot of the asymmetries in vowel discrimination of vervets
from Sinnott (1989).Arrows represent the direction of change that was
easier to discriminate. For macaques, only the A-2contrast was easier to
discriminate than the 2-Acontrast. F1 and F2 values of vowel tokens are
those reported in Sinnott (1989).
1989). Decreased sensitivity to pure tones at lower frequencies
of less than 1.0 kHz has also been reported in monkeys com-
pared to humans (Owren et al., 1988). Consequently, perceptual
asymmetries involving back vowel contrasts may simply reflect the
difficulty that monkeys have if the decrease in F2 from the stan-
dard to comparison vowel is perceived as a decrease in intensity.
When vowel detection thresholds of humans and monkeys are
most similar (i.e., for the front vowels /i/ and /I/; Sinnott, 1989),
vervets show the same directional asymmetry as human infants
(Swoboda et al., 1978;Dejardins and Trainor, 1998). Therefore,
we might expect infants to show a similar directional asymmetry
when tested on low back contrasts if they also perceive decreases in
F2 as decreases in vowel intensity. This is because infants, like mon-
keys, are unable to discriminate stimuli that decrease in intensity
(Sinnott and Aslin, 1985).
Therefore, to demonstrate that the directional asymmetries
proposed by Polka and Bohn’s (2011) natural referent vowel
framework are exclusive to humans, we see an absolute need for
more studies on humans and animals that use identical stimuli
and comparable experimental designs in order to enable between-
species comparisons of asymmetries in vowel perception. In
particular, we encourage studies in human infants that test for per-
ceptual asymmetries between low back contrasts that have already
been examined in animals, such has the /U/–/A/ contrast (where
cats, red-winged blackbirds, and monkeys find the change from /U/
to /A/ easier than the change from /A/to/U/), and the /u/ – /U/ and
/A/–/2/ contrasts (where monkeys’ performances contradict the
predictions of the central-to-peripheral asymmetry hypothesis).
Lastly, to properly delineate the function of perceptual asymme-
tries in vowel perception in humans, we must also understand
the causes and possible functions of directional asymmetries in
auditory perception in animals. For example, do animals exhibit
directional asymmetries in detecting a change in their species-
specific communication, and do they make use of these perceptual
asymmetries? Or are directional asymmetries a by-product of
properties of auditory systems (and thus have no functional use)?
Regardless of whether directional biases in vowel perception
are found to be uniquely human, general perceptual biases in
human audition may further our understanding of the existence
of vowel asymmetries. Various auditory perceptual biases have
been found, such as sounds with increasing intensity being per-
ceived as closer than sounds than sounds with decreasing intensity
(Neuhoff, 1998), ramped sounds being perceived as having greater
intensity and longer duration than damped sounds (Irino and
Patterson, 1996;Schlauch et al., 2001), and frequency modulated
sounds being easier to detect among pure tones distractors than
the reverse (Cusack and Carlyon, 2003). Some of these asym-
metries appear to have plausible evolutionary explanations. For
instance, rising harmonic sound intensities are reliable indicators
of an approaching sound source, thus humans and monkeys per-
ceive the source as being closer than reality when sound intensity
increases (but not decreases) in order to account for a“margin of
safety” (Neuhoff, 1998;Ghazanfar et al., 2002).
SPEAKER VOICE RECOGNITION
The speech signal not only contains linguistic information, but
also nonlinguistic information about the speaker from his/her
www.frontiersin.org January 2015 |Volume 5 |Article 1543 |3
Kriengwatana et al. Revisiting vocal perception in animals
voice, such as age, gender, and socio-linguistic background. Voices
are sounds generated by vibrations of the vocal folds in the lar-
ynx, which are then modified by the vocal tract, leading to an
enhancement of particular frequencies (i.e., formant frequencies).
The fundamental frequency and formant frequencies in a per-
son’s voice are influenced by the size of their vocal folds and
vocal tract, which is why men, with their larger vocal folds and
vocal tract, tend to have lower fundamental frequencies and for-
mant frequencies than women and children (reviewed in Belin
et al., 2004;Latinus and Belin, 2011). Voice differences between
speakers may be related to slight variations in the vocal apparatus
of different individuals. Differences in the way the vocal appa-
ratus is used, either intentionally or inadvertently, contributes
to the distinctiveness of voices. For example, nasal voices are
produced when the velum is in a slightly lowered position and
breathy voices are produced when the vocal folds remain slightly
parted during speaking (see Story and Titze, 2002). Human
adults can reliably detect a speaker’s approximate age, gender,
and accented speech (Hartman, 1979;Flege, 1984;Mullennix
et al., 1995;Bachorowski and Owren, 1999), and can also identify
familiar speakers from hearing their voices (Bricker and Pruzan-
sky, 1976). Importantly, speaker voice characteristics interact
with linguistic comprehension during speech perception: famil-
iar speakers elicit better performance in a word identification task
than unfamiliar speakers (Nygaard and Pisoni, 1998), and vowel,
word, and consonant-vowel identification are more accurate in
single speaker compared to multiple speaker conditions (Strange
et al., 1976,1983;Assmann et al., 1982;Magnuson and Nusbaum,
2007). Knowledge of a speaker’s accent and gender also increases
word and vowel identification accuracy, respectively (Johnson,
2005;Trude and Brown-Schmidt, 2012;Smith, 2014). Conse-
quently, a complete account of how humans perceive speech also
requires consideration of the role that voices play in influencing
speech perception.
Perceiving speaker identity from voice information is impor-
tant for human social interactions. In adults, mechanisms involved
in analyzing linguistic and speaker information appear to be par-
tially dissociable (reviewed in Belin et al., 2004,2011;Belin, 2006).
Neuroimaging studies demonstrate that the brain can differenti-
ate “who” from “what” is being said (Formisano et al., 2008), and
cortical regions in the mid and anterior superior temporal gyrus
respond selectively to human voices and are sensitive to speaker
identity (Imaizumi et al., 1997;Belin et al., 2000;Nakamura et al.,
2001;Belin and Zatorre, 2003;von Kriegstein et al., 2003). For
pre-linguistic infants, extracting the identity of the speaker is
likely just as important as deciphering meaning in speech. Even
in utero, infants respond differently to the voice of their mother
compared to a stranger (Kisilevsky et al., 2003), and behavioral
and neuroimaging findings confirm that very young infants can
indeed discriminate their mother’s voice from a stranger’s voice
(DeCasper and Fifer, 1980;Dehaene-Lambertz et al., 2010), their
father’s voice from other males (DeCasper and Prescott, 1984), and
male from female voices (Jusczyk et al., 1992). Interestingly, the
age at which infants become able to identify voices of individuals
other than their mother’s remains unsettled (Brown, 1979;Hepper
et al., 1993;Kisilevsky et al., 2003,2009;Lee and Kisilevsky, 2014).
In any case, these studies indicate that specialization for processing
human voices appears to develop over infancy in conjunction
with language experience (Grossmann et al., 2010;Vouloumanos
et al., 2010;Johnson et al., 2011;Friendly et al., 2014;Schultz et al.,
2014).
Humans are not the only species that can extract different types
of information from conspecific vocalizations. The ability to dis-
tinguish and recognize individual conspecifics in the context of
neighbor-stranger recognition has been found in numerous ani-
mals (including invertebrates) across the entire animal kingdom
(see Tibbetts and Dale, 2007). For instance, Kentucky warblers
and hooded warblers know both identity and location of each of
their neighbors, and will respond aggressively to neighbor songs
that are broadcasted at incorrect territorial boundaries (Godard,
1991;Godard and Wiley, 1995). Female great tits can discrim-
inate between the highly similar songs of their mate and male
neighbors (Blumenrath et al., 2007), and may eavesdrop on ter-
ritorial mate-neighbor singing interactions in order to assess
potential extra-pair partners (Otter et al., 1999). Vocal kin recog-
nition has also been repeatedly demonstrated in various birds
and mammals (e.g., Rendall et al., 1996;Holekamp et al., 1999;
McComb et al., 2000;Illmann et al., 2002;Sharp et al., 2005;
Janik et al., 2006;Akçay et al., 2014). Parent-offspring recogni-
tion by non-nesting penguins such as the king penguin offers
a very strong case of vocal recognition because the chicks must
accurately identify the calls of its parents within a crowded and
noisy colony with almost no aid from visual or spatial cues.
To identify parents, king penguin chicks pay attention to fre-
quency modulations over time in conjunction with a beat analysis
(Jouventin et al., 1999;Aubin et al., 2000). In contrast, chicks
of nesting penguin species, such as Adelie penguin and gen-
too penguin, that can use nesting site as an additional cue for
parent identification will use simpler identification mechanisms
that rely primarily on pitch and ignore frequency modulations
(Jouventin and Aubin, 2002).
The difference between nesting and non-nesting penguins
described above highlights the fact that individual recognition
by auditory means may be achieved in many ways depending
on ecological pressures and evolutionary history. For instance,
birds can recognize a conspecific by the songs in his repertoire,
by a particular variation in his song, or by his voice characteris-
tics (Weary and Krebs, 1992). European starlings that each have
a large song repertoire do not recognize other individual star-
lings by voice characteristics but rather by memorizing song motifs
of different individuals (Gentner and Hulse, 1998;Gentner et al.,
2000). On the other hand, great tits also possess a song repertoire
but rely on voice characteristics to identify conspecific individuals
(Weary and Krebs, 1992). In these experiments, recognition was
assessed by training birds to discriminate songs from two indi-
viduals and testing their ability to discriminate other previously
unheard songs from the same individuals (Weary and Krebs, 1992;
Gentner and Hulse, 1998;Gentner et al., 2000). Animals are also
capable of heterospecific vocal recognition of familiar individu-
als, as demonstrated in some monkey species that differentiated
between the vocalizations of familiar and unfamiliar members of
other monkey species (Candiotti et al., 2013). Observations like
this suggests that animals may also be able to distinguish different
humans based on their voice characteristics.
Frontiers in Psychology |Language Sciences January 2015 |Volume 5 |Article 1543 |4
Kriengwatana et al. Revisiting vocal perception in animals
Identification of particular human individuals can be useful
for animals because they can behave adaptively toward threaten-
ing and unthreatening humans by interrupting normal behavior
or ignoring them, respectively. Visual discrimination and recog-
nition of individual humans has been documented in several
animals such as the magpie (Pica pica; Lee et al., 2011), mock-
ingbird (Mimus polyglottos; Levey et al., 2009), crow (Corvus
brachyrynchos; Marzluff et al., 2010,2012), and octopus (Ente-
roctopus dofleini;Anderson et al., 2010). Some evidence also
exists that animals raised in close contact with humans can
distinguish between different human voices, which we have
summarized in Table 1. In most of these studies, recognition
was measured by preferential looking times when animals were
presented with human faces and a voice that did or did not
match one of the faces being shown. The design and interpre-
tation of these studies are similar to those reported for infant
studies (see Houston-Price and Nakai, 2004): longer looking
times when faces and voices were mismatched were taken as
an indication that subject’s expectations about the relationship
between speaker face and speaker voice (i.e., speaker identity) were
violated.
Of the studies in Ta b le 1, only Sliwa et al. (2011) and Proops
and McComb (2012) have shown that animals can identify human
individuals by their voices because the researchers tested dis-
crimination among multiple familiar humans. This is critically
important for proving individual identification, as discriminat-
ing familiar from unfamiliar individuals is recognition at the
class-level, not the individual level (Tibbetts and Dale, 2007). In
our opinion, however, even these two studies do not definitively
prove human voice recognition because they used the animal’s
name or phrases that the animal may have been frequently exposed
to. This could lead animals to form an association between the spe-
cific phrase(s) and the speaker, such that they may not generalize
their recognition to novel utterances by the speaker. Thus, animals’
performances in these studies may not necessarily reflect genuine
recognition of different human speakers based on voice charac-
teristics. We encourage future studies in human voice recognition
to incorporate this method of training (i.e., initial discrimina-
tion between sounds from two familiar speakers and then testing
their ability to recognize different sounds from the same speakers)
because it eliminates class-level recognition and learned associa-
tions between speaker and specific phrases as confounding factors.
Alternatively, researchers may also consider using a habituation-
dishabituation paradigm, where subjects are habituated to various
speech sounds from one speaker and then tested on whether they
dishabituate to speech sounds of a different speaker (e.g., Johnson
et al., 2011).
Another fundamental component that these studies do not
address is what auditory cues animals may be using to discrim-
inate different human voices, and whether they use the same
cues to identify conspecific calls. The question of which cues are
used to identify speakers is highly relevant to humans as well,
as there is currently no consensus on this matter (see Creel and
Bregman, 2011). Some studies have found that adults use pitch
and/or formants to identify speakers (e.g., Remez et al., 1987;
Fellowes et al., 1997;Baumann and Belin, 2010), whereas others
Table 1 |List of studies that have tested animals’ discrimination of different human voices.
Reference Species Method Comparison Stimulus
Adachi etal. (2007) Dogs Face-voice matching FvU Animal’s name
Sliwa et al. (2011) Rhesus macaques Face-voice matching FvF Six standardized phrases
(e.g., “bonjour tout le monde”, “voila”)
Lampe and Andre (2012) Horses Live person-voice matching FvU Standardized phrase
“Hey, [animal’s name], what are you doing
there? Are you having a good day today? We
have many riding lessons this week don’t we?
The semester has started at JMU. You be a
good boy/girl today!”
Proops and McComb (2012) Horses Live person-voice matching FvU
FvF
Animal’s name
Wascher etal. (2012) Crows Playback FvU “Hey”
Saito and Shinozuka (2013) Cats Habituation–dishabituation FvU Animal’s name
Ratcliffe etal. (2014) Dogs Live person-voice matching Male vs. female Four standardized phrases
“Hey!”, “Come on then”, “Good dog!”, “What’s
this?”
McComb et al. (2014) Elephants Playback Male vs. female
Man vs. boy
Masaai vs. Kamba
standardized sentence
“Look, look over there, a group of elephants is
coming”
*Note: FvU, familiar versus unfamiliar voice, FvF, familiar versus familiar voice.
www.frontiersin.org January 2015 |Volume 5 |Article 1543 |5
Kriengwatana et al. Revisiting vocal perception in animals
have suggested that these spectral cues are important for gen-
der determination while temporal patterns are used for individual
identification (Fellowes et al., 1997). Furthermore, not all listeners
use the same cues to distinguish voices, and different cues may
be more important for distinguishing particular voices (Kreiman
et al., 1992).
We are not aware of any studies that investigate what acous-
tic cues animals may be using to discriminate or identify human
voices, although this is surely a question that merits rigorous inves-
tigation. Work by Zoloth et al. (1979) suggests that conspecifics
and heterospecifics may attend to different cues, as Japanese
macaques used peak of a frequency inflection while other monkey
species used initial pitch to discriminate between coos of other
Japanese macaques. But if animals use the same cues for recogni-
tion of conspecific vocalization as heterospecific vocalization, then
we expect that only some species will use voice characteristics for
individual recognition. That is, following the example described
above, we would expect great tits but not European starlings to
recognize different human voices because great tits discriminate
conspecifics based on voice characteristics while starlings discrim-
inate conspecifics based on song motifs (Weary and Krebs, 1992;
Gentner and Hulse, 1998;Gentner et al., 2000). Even then, great
tits may rely on different parameters than human listeners, as the
song parameters that show significant variation between individ-
ual great tits are the number of phrases in a song, duration of the
first phase minus the last phase, maximum frequency, and pitch
(Weary, 1990;Weary et al., 1990). The acoustic similarities between
human speech and species-specific vocalizations may also deter-
mine which cues are used. For example, zebra finches distance
calls have harmonic structures that resemble vowel formants in
human speech (Dooling et al., 1995). This similarity may explain
why zebra finches perform similarly to humans during discrimi-
nation of speech sounds (Dooling et al., 1995;Ohms et al., 2012),
and why neurons in a secondary auditory area of the zebra finch
brain respond more strongly to human speech and species-specific
calls than calls of other songbirds that are acoustically less similar
(Chew et al., 1996).
Findings from animal studies are valuable for understand-
ing the extent to which human voices can be differentiated and
recognized without the need for human voice-specific neural net-
works (Leaver and Rauschecker, 2010;Belin et al., 2011). However,
research on human voice processing in animals to date is scarce,
and of the studies that do exist, the ability to recognize voices
(defined as discriminating between different familiar voices, as
opposed to discriminating between familiar and unfamiliar voices)
has yet to be compellingly demonstrated. An understanding of
the differences and similarities of acoustic cues and mechanisms
used for acoustic recognition of conspecifics and heterospecifics
is also currently severely lacking. We strongly believe that these
issues must be addressed in future studies if we are to dis-
cover parallels between voice processing in humans and animals,
and consequently shed light onto the evolution of human voice
perception.
SPEAKER NORMALIZATION
The counterpart of being able to extract information about speaker
identity is being able to handle acoustic variations of the same
utterance caused by speaker differences. The acoustic realizations
of phonemes and words can vary tremendously between speakers,
due to physical, contextual, environmental, and sociolinguistic
factors (i.e., age and gender differences in vocal tract size and
shape, coarticulation, background noise, and accents). Conse-
quently, speaker normalization refers to our ability to recognize
phonologically identical utterances despite high acoustic variabil-
ity across speakers (Johnson, 2005). A compelling example of the
immense variability in the speech signal resulting from differences
between speakers is in vowel production.Vowels arereliably distin-
guished by the first and second formant frequencies (F1 and F2);
however, F1 and F2 values of vowels produced by different speakers
(and especially different genders) are highly variable within a vowel
category and greatly overlap between categories, to the extent that
the acoustic distance within a vowel category can be just as large as
the acoustic distance between vowel categories (Potter and Stein-
berg, 1950;Peterson and Barney, 1952;Hillenbrand et al., 1995).
Consequently,studies that seek to understand our impressive abil-
ity to normalize vowels despite this intensive overlap (Peterson
and Barney, 1952;Strange et al., 1976,1983;Assmann et al., 1982)
can provide convincing evidence of what processes contribute to
speaker normalization.
Researchers have not yet reached a consensus on how vowel
normalization in humans is achieved (reviewed in Nearey, 1989;
Johnson et al., 1999;Adank, 2003;Johnson, 2005). Some argue
that normalization occurs via low-level auditory perceptual pro-
cesses, by computation of particular formant ratios that allow
vowel categories to be distinctively represented in discrete regions
in acoustic space (Potter and Steinberg, 1950;Syrdal and Gopal,
1986;Miller, 1989), or by using F0 or F3 values (i.e., fundamen-
tal frequency and third formant frequency) that are correlated
with vocal tract length to disambiguate ambiguous F1 and
F2 values (e.g., Ladefoged and Broadbent, 1957;Fujisaki and
Kawashima, 1968;Wakita, 1977;Nearey, 1989). A recent paper
suggests that humans normalize for speaker differences by com-
puting ratios between F1 and F2 in relation to F3. Specifically,
Monahan and Idsardi (2010) showed that transforming F1 and F2
values into F1/F3 and F2/F3 ratios effectively eliminated variation
between speakers in a corpus of American English vowels from
Hillenbrand et al. (1995). They also provided neurophysiologi-
cal evidence that the human brain is sensitive to F1/F3 ratios,
complementing prior work showing that the brain is sensitive
to F2/F3 ratios (Monahan and Idsardi, 2010). Alternatively, oth-
ers argue that listeners form rich perceptual representations of
speaker identity by incorporating vocal tract length with other
learned factors such as familiarity or socio-cultural expectations;
these abstract speaker representations subsequently influence
vowel normalization (i.e., “talker normalization”; Johnson, 1990;
Johnson et al., 1999).
Both types of views have merits and drawbacks, and they have
also both received empirical support. The auditory perceptual
approaches can account for how vowel normalization occurs with
limited linguistic capabilities and familiarity with novel speakers
(Monahan and Idsardi, 2010). Behavioral and neurophysiologi-
cal studies indicate that humans normalize speaker differences in
vowels without linguistic comprehension or attention. In adults,
extraction and processing of vowel formants takes place at a
Frontiers in Psychology |Language Sciences January 2015 |Volume 5 |Article 1543 |6
Kriengwatana et al. Revisiting vocal perception in animals
subcortical and pre-attentional level (von Kriegstein etal., 2006;
Monahan and Idsardi,2010;Tuomainen et al., 2013), and that even
pre-linguistic infants can categorize vowels of different speakers
and genders (Kuhl,1983). On the other hand, talker normalization
approaches explain how listeners can learn speaker-specific and
language-specific patterns of speech (Johnson et al., 1999). Several
findings support the idea that learning of non-acoustic speaker-
related variables is indeed involved in accommodating for speaker
differences in phonetic realizations (Samuel and Kraljic, 2009).
For instance, expectations of speaker gender can alter phoneme
boundaries (Johnson et al., 1999), single speaker and familiar
speakers conditions yield better vowel identification (Strange et al.,
1976,1983;Assmann et al., 1982;Mullennix et al., 1989;Nygaard
and Pisoni, 1998), and infants and adults can rapidly adapt to
accented speech (Clarke and Garrett, 2004;Bradlow and Bent,
2008;White and Aslin, 2011;Cristia et al., 2012;van Heugten and
Johnson, 2014)
Comparative studies in animals represent one way to address
whether speaker normalization mechanisms are unique to
humans. Although normalization is necessary for word recogni-
tion, normalization also occurs for phonetic segments. Indeed,
normalization has been demonstrated in 6 month-old infants
before they acquire words, and at the level of vowels (Kuhl, 1983).
That is, non-verbal infants can normalize speech even before they
have learned words. Even for the few words that 6–9 month-old
infants do seem to recognize (Bergelson and Swingley, 2012), nor-
malization may not have been required for recognition, since
the words were spoken by a familiar speaker (i.e., a parent).
Therefore, it is important to discern what perceptual processes
infants use to normalize speech, and whether these mechanisms
are rudimentary processes that are available to infants because they
are species-shared or non-speech related perceptual mechanisms.
Unfortunately, only a handful of animal studies have considered
speaker variability as a factor, even though the ability to account
for speaker-dependent variation is fundamental for speech percep-
tion. A possible reason for lack of interest in how animals handle
speaker-dependent variation in speech may have to do with skep-
ticism regarding what, if any, benefits this investigation would
yield. In other words, as suggested by Trout (2001), what reason
would an animal have to normalize speaker variation in speech?
What advantages would it confer to the animal? And even if ani-
mals do appear to normalize speech, are they applying similar
mechanisms to humans? We argue that studying speaker nor-
malization in non-human animals is ecologically valid because
animals also have to deal with signal variability when recogniz-
ing vocalizations made by other individuals of the same species
(conspecifics) and other individuals of a different species (het-
erospecifics). On the other hand, whether animals and humans
attend to the same cues and have shared mechanisms for normal-
izing human speech is an open and exciting question that is yet to
be answered.
Signal variability in animal vocalizations can be caused by
inter-individual differences, such as physical size (Fitch, 1997,
1999;Growcott et al., 2011), intra-individual differences, such
as affective state (e.g., stress; Perez et al., 2012), and a combina-
tion of inter-and intra-individual differences such as fluctuations
in endocrine state (Galeotti et al., 1997;Soma et al., 2002). Yet
animals must still be able to acquire information about the type of
vocalization (such as calls indicating predator versus food source)
and in some contexts, the identity of the signaler. Thus, in par-
allel to how humans can extract linguistic information despite
speaker-dependent variation in the speech signal, animals can also
categorize vocalizations of conspecific as well as heterospecific
vocalizations despite individual variation in the signal. Indeed,
responding to hetereospecific signals is widespread in many ani-
mals because of the advantages it confers to the receiver (Seppänen
et al., 2007). For example, red-breasted nuthatches (Sitta canaden-
sis) are sensitive to variations in black-capped chickadee (Poecile
atricapillus) mobbing calls that encode information about the size
and degree of threat of predators (Templeton and Greene, 2007),
avian brood parasites may eavesdrop on sexual signals of host
species to assess parental quality (Parejo and Avilés, 2007), and
hornbills can respond to differentially to alarm calls of Diana
monkeys that signal significant and non-significant threats for the
hornbills (Rainey et al., 2004).
The red-breasted nuthatches’ extraction of information from
the black-capped chickadee chick-a-dee call is particularly com-
pelling because of the highly sophisticated nature of this vocal-
ization, both at a contextual and an acoustic level. In addition to
signaling predators, the chick-a-dee call is used in other contexts,
such as to maintain group cohesion and coordinate group move-
ments (Ficken et al., 1978). Significant individual differences in
the chick-a-dee call can occur in every 100-Hz interval between
500 and 7000 Hz, with greater variation between individuals than
within individuals of the same group in various temporal and
spectral parameters (Mammen and Nowicki, 1981). Acoustically,
the call is made of four note types (A, B, C, D) sung in a fixed
sequence, but note types can be repeated or omitted to create 100s
of variations such as ACCDD, AABBCD, or ADDDD (Hailman
et al., 1985). Black-capped chickadees can also modify spectral
components of the D note so that this note converges amongst
members of the same group (Nowicki, 1989).
Importantly, the same variations in syntax (number of D
notes), temporal and spectral characteristics (duration and inter-
val between D notes, frequency overtone spacing and bandwidth)
are also used to convey information about predator threat (Te m -
pleton et al., 2005). That is, the same acoustic properties that
encode predator threat also vary depending on the individual.
Yet despite the apparent overlap between acoustic parameters that
signal individual/group identity and predator threat, nuthatches
are still able to obtain information relevant for their behaviors.
Thus, this constitutes a naturally occurring example of normaliza-
tion of heterospecific vocal signals by a non-human animal (i.e.,
disregarding irrelevant variation caused by individual differences
in the vocalizations of another species). In this light, the idea that
non-human animals can account for speaker differences in human
vocalizations seems quite plausible, and in the following sections
we review studies that suggest that speaker normalization of speech
is not a uniquely human ability.
The ability to normalize speaker differences in naturally spoken
vowels or correlates of gender differences in synthetic vowels (i.e.,
F0, which is generally higher in female than male voices and is uti-
lized in perception of voice gender by humans; Hillenbrand et al.,
1995;Mullennix et al., 1995;Lavner et al., 2000) has been tested
www.frontiersin.org January 2015 |Volume 5 |Article 1543 |7
Kriengwatana et al. Revisiting vocal perception in animals
in cats, rhesus monkeys, dogs, chimpanzees, chinchillas, budgeri-
gars, rats, and ferrets (Dewson, 1964;Dewson et al., 1969;Baru,
1975;Burdick and Miller, 1975;Kojima and Kiritani, 1989;Dool-
ing and Brown, 1990;Eriksson and Villa, 2006;Bizley et al., 2013).
All of these studies reported that animals were able to differenti-
ate stimuli based on vowel category and ignore speaker-dependent
variation. However, we argue that none of these studies robustly
demonstrate speaker normalization. This is because the experi-
ments on cats, dogs, rhesus monkeys, chimpanzees, chinchillas,
and budgerigars tested discrimination of the vowels /i/, /u/, and
or /a/ (Dewson, 1964;Dewson et al., 1969;Baru, 1975;Burdick
and Miller, 1975;Kojima and Kiritani, 1989). As these vowels
occupy distant acoustic spaces, the variability between these vowel
categories is likely larger than the variability between speakers.
Consequently, a stronger test for vowel normalization would use
vowel categories where speaker differences and vowel category dif-
ferences have relatively equal variation. This was addressed by
Dooling and Brown (1990), who found that budgerigars could
discriminate between the psychoacoustically closer vowels /i/ and
/E/ produced by different male speakers. However, they did not
examine whether budgerigars could also discriminate these vow-
els produced by different female speakers, so we cannot be sure
that budgerigars can in fact normalize these vowels because much
of the acoustic overlap between vowel categories are due to gender
differences (see Peterson and Barney, 1952). Lastly, the experi-
ments in rats, ferrets, and chimpanzees used synthetic vowels that
differed only in one acoustic parameter (Kojimaand Kiritani, 1989;
Eriksson and Villa, 2006;Bizley et al., 2013). This is problematic
for conclusions about speaker normalization because voices differ
in various dimensions, and no single acoustic cue has been found
that reliably predicts speaker characteristics that can be used to
normalize vowels.
As far as we know, Ohms et al. (2010) are the only researchers
that have clearly demonstrated that an animal can normalize vow-
els of different speakers. Specifically, Ohms et al. (2010) found that
zebra finches can generalize their discrimination of two words that
differ only in vowels (wIt and wEt) to multiple, different male or
female speakers after being trained to discriminate these words
from a single speaker of the same sex. Their results show that birds
are indeed learning something about the phonemic differences
between wIt and wEt, and are able to apply these criteria to unfa-
miliar speakers while ignoring speaker-dependent differences in
production of these words. Notably, zebra finches could also rec-
ognize the same word produced by male and female speakers after
learning the word from a set of speakers of the other sex (Ohms
et al., 2010; see also ten Cate, 2014). Remarkably,this ability seems
lacking in human infants (Houston and Jusczyk, 2000). A logical
follow up of these results would be a test for normalization of iso-
lated vowels – an ability demonstrated by human adults (Strange
et al., 1976,1983;Assmann et al., 1982). This is because the birds
in Ohms et al. (2010) could have been using other acoustic cues
instead of vowel differences during generalization, such as for-
mant transitions between consonant and vowel. Recently, a study
by Engineer et al. (2013) reported that rats too could normalize
speaker variation in consonants. Rats could learn to discriminate
between the words dad and tad produced by a female speaker and
generalize this discrimination to novel male and female speakers.
With the same stimuli, rats could also learn to distinguish between
the word dad spoken by a female speaker and the same word that
was pitch-shifted down by one octave, and subsequently general-
ize this discrimination to novel male and female voices (Engineer
et al., 2013). This shows that, like humans, animals can extract
different types of information from speech (see section on speaker
voice recognition).
Griebel and Oller (2012) provide another interesting case that
may potentially reflect normalization of speaker differences by a
Yorkshire terrier (Bailey). They found that Bailey could correctly
retrieve 13 out of 16 familiar toys when verbally requested by a
female experimenter with a German accent and a male exper-
imenter with a western American English (California) accent,
even though Bailey’s owner was female with a southern Amer-
ican English (Tennessee) accent. Bailey’s accurate performance
with these accented voices was not due to training or familiar-
ity, as the experimenters had never previously requested the toys
from Bailey. Again, we do not know which acoustic parameters
Bailey was using to recognize familiar words spoken by unfamil-
iar speakers. The authors note that toy names often consisted of
“two or more words that included intonation and alliteration or
assonance cues that may have made them easier to remember
and discriminate” (Griebel and Oller, 2012). This suggests that
Bailey may not have needed to normalize speaker differences in
vowel production in order to recognize the words, but possibly
relied on prosodic cues – another feature in speech that tamarins
(Ramus et al., 2000), rats (Toro et al., 2003), Java sparrows (Naoi
et al., 2012), and zebra finches (Spierings and ten Cate, 2014)are
sensitive to.
Other studies on word discrimination in dogs have been con-
ducted, but do not offer clear evidence for speaker normalization.
This is because these studies do not control for non-verbal cues
from the trainer that dogs could rely on to perform correct actions
(see Mills, 2005), or they test dogs’ ability to retrieve objects
from the verbal commands of a single familiar trainer (Warden
and Warner, 1928;Kaminski et al., 2004;Fukuzawa et al., 2005).
Another study did not explicitly state in the methods whether com-
mands were consistently given by a single trainer or by multiple
trainers (Ramos and Ades, 2012). In a similar vein, Warfield et al.
(1966) showed that cats could discriminate the words “bat” and
“cat,” but they did not test whether discrimination was affected if
word tokens were produced by multiple speakers.
Responding to categories of heterospecific communication sig-
nals is commonly found in the animal kingdom, and though
few studies provide direct evidence, there is some indication that
animals may be able to normalize speaker differences in human
speech. Yet replication and extension of positive findings such as
those by Ohms et al. (2010) and Engineer et al. (2013) are com-
pulsory. In particular, we point out that the ability to categorize
speech sounds from different speakers and disregard non-essential
information is not an absolute demonstration of normalization,
which is why researchers must test whether animals and humans
apply the same normalization mechanisms. For example, do both
humans and animals successfully categorize vowels of multiple
speakers by computing formant ratios as proposed by Monahan
and Idsardi (2010), or by using other normalization algorithms
that have been previously proposed (reviewed in Escudero and
Frontiers in Psychology |Language Sciences January 2015 |Volume 5 |Article 1543 |8
Kriengwatana et al. Revisiting vocal perception in animals
Bion, 2007). Such tests would be invaluable in verifying whether
similar behaviors exhibited by humans and animals are mediated
by the same or different mechanisms.
CONCLUSION
In this review we have discussed the current state of animal
research in three aspects of speech and voice perception. We have
presented arguments and evidence that caution against prema-
ture conclusions about whether asymmetries in vowel perception
reflect an innate and uniquely human bias that is present in
inexperienced language learners and not attributable to general
properties of the vertebrate or mammalian auditory system. We
have noted that there is a lack of definitive evidence for animal
recognition of individual human voices in the literature, and we
have suggested ways to improve experimental designs that will
more assuredly test whether animals can use voice characteris-
tics to discern different humans. Lastly, we infer with reservation
from two recent experiments that animals may be able to nor-
malize speaker differences. Consequently, we strongly encourage
researchers to conduct more carefully designed and rigorously
controlled experiments to validate the human-specific claims of
asymmetries in vowel perception, voice perception, and speaker
normalization that we have described. Studies that identify what
acoustic cues animals rely on to perform either individual voice
perception or speaker normalization are also seriously needed as
they are invaluable for our understanding of how these behaviors
are accomplished.
With accumulating empirical results, we can sooner reach the
stage where findings from these three areas can be synthesized to
tackle broader questions in speech perception. An example would
be whether and at what level of processing speaker identification
and speaker normalization mechanisms interact during speech
perception. Some researchers believe that in humans the analysis
of linguistic information and speaker identity during speech per-
ception may be segregated into dissociable but interacting neural
pathways (although the stage at which the integration of these two
streams occurs is undetermined; Belin et al., 2004). Comparative
research on whether animals also analyze conspecific vocalizations
and/or human speech for communicative content and signaler
identity separately would reveal whether or not this compartmen-
talization occurred as a distinctive human adaptation that enables
us to map overlapping and highly variable acoustic information
onto correct phonetic categories while simultaneously processing
speaker identity related cues.
We have emphasized throughout this paper that address-
ing these topics in animals is neither insignificant nor extra-
neous because many social animals encounter similar chal-
lenges to those humans face when discriminating similar-
sounding vocalizations/phonemes, determining signaler/speaker
characteristics from vocalizations/speech, and resolving between-
individual variation in order to perceive the content of vocal-
izations/speech. It is our hope that this review will have
cogently demonstrated that expanding our view to include how
animals perceive speech can offer valuable insights for more
thorough conceptualization of the specificity, simplicity (or
complexity), and specialization of human speech perception
mechanisms.
ACKNOWLEDGMENT
We would like to thank Gabriël Beckers for comments on an
earlier version of this manuscript. This research was supported
by Australian Research Council grant DP130102181 (CI Paola
Escudero).
REFERENCES
Adachi, I., Kuwahata, H., and Fujita, K. (2007). Dogs recall their owner’s face upon
hearing the owner’s voice. Anim. Cogn. 10, 17–21. doi: 10.1007/s10071-006-
0025-8
Adank, P. (2003). Vowel Normalization: a Perceptual-Acoustic Study of Dutch Vowels.
Ph.D. thesis, University of Nijmegen, Nijmegen, The Netherlands.
Akçay, Ç., Hambury, K. L., Arnold, J. A., Nevins, A. M., and Dickinson, J. L. (2014).
Song sharing with neighbours and relatives in a cooperatively breeding songbird.
Anim. Behav. 92, 55–62. doi: 10.1016/j.anbehav.2014.03.029
Anderson, R. C., Mather, J. A., Monette, M. Q., and Zimsen, S. R. M. (2010).
Octopuses (Enteroctopus dofleini) recognize individual humans. J. Appl. Anim.
Welf. Sci. 13, 261–272. doi: 10.1080/10888705.2010.483892
Assmann, P. F., Nearey, T. M., and Hogan, J. T. (1982). Vowel identification: ortho-
graphic, perceptual, and acoustic aspects. J. Acoust. Soc. Am. 71, 975–989. doi:
10.1121/1.387579
Aubin, T., Jouventin, P., and Hildebrand, C. (2000). Penguins use the two-
voice system to recognize each other. Proc. R. Soc. Lond. 267, 1081–1087. doi:
10.1098/rspb.2000.1112
Bachorowski, J. A., and Owren, M. J. (1999). Acoustic correlates of talker sex
and individual talker identity are present in a short vowel segment produced
in running speech. J. Acoust. Soc. Am. 106, 1054–1063. doi: 10.1121/1.427115
Baru, A. V. (1975). “Discrimination of synthesized vowels [a] and [i] with varying
parameters (Fundamental frequency, intensity, duration and number of for-
mants) in dog,” in Auditory Analysis and Perception of Speech, eds G. Fant and
M. A. A. Tatham (Waltham, MA: Academic Press), 91–101.
Baumann, O., and Belin, P. (2010). Perceptual scaling of voice identity: common
dimensions for different vowels and speakers. Psychol. Res. 74, 110–120. doi:
10.1007/s00426-008-0185-z
Beckers, G. J. L. (2011). Bird speech perceptionand vocal production: a comparison
with humans. Hum. Biol. 83, 191–212. doi: 10.3378/027.083.0204
Belin, P. (2006). Voice processing in human and non-human primates. Philos. Trans.
R. Soc. Lond. B Biol. Sci. 361, 2091–2107. doi: 10.1098/rstb.2006.1933
Belin, P., Bestelmeyer, P. E. G., Latinus, M., and Watson, R. (2011). Under-
standing voice perception. Br. J. Psychol. 102, 711–725. doi: 10.1111/j.2044-
8295.2011.02041.x
Belin, P., Fecteau, S.,and Bédard, C. (2004). Thinking the voice: neural correlates of
voice perception. Trends Cogn. Sci. 8, 129–35. doi: 10.1016/j.tics.2004.01.008
Belin, P., and Zatorre, R. J. (2003). Adaptation to speaker’s voice in right anterior
temporal-lobe. Neuroreport 14, 2105–2109. doi: 10.1097/00001756-200311140-
00019
Belin, P., Zatorre, R. J., Lafaille, P., Ahad, P., and Pike, B. (2000). Voice-selective areas
in human auditory cortex. Nature 403, 309–12. doi: 10.1038/35002078
Bergelson, E., and Swingley, D. (2012). At 6-9 months, human infants know the
meanings of many common nouns. Proc. Natl. Acad. Sci. U.S.A. 109, 3253–3258.
doi: 10.1073/pnas.1113380109
Best, C. T., and Faber,A. (2000). “Developmental increase in infants’ discrimination
of nonnative vowels that adults assimilate to a single native vowel,” in Paper
presented at the International Conference on Infant Studies, Brighton, 16–19.
Bizley, J. K., Walker, K. M. M., King, A. J., and Schnupp, J. W. H. (2013). Spectral
timbre perception in ferrets: discrimination of artificial vowels under different
listening conditions. J. Acoust. Soc. Am. 133, 365–376. doi: 10.1121/1.4768798
Blumenrath, S. H., Dabelsteen, T.,and Pedersen, S. B. (2007). Vocal neighbour–mate
discrimination in female great tits despite high song similarity. Anim. Behav. 73,
789–796. doi: 10.1016/j.anbehav.2006.07.011
Bohn, O.-S., and Polka, L. (2014). Fast phonetic learning in very young
infants: what it shows and what it doesn’t show. Front. Psychol. 5:511. doi:
10.3389/fpsyg.2014.00511
Bradlow, A. R., and Bent, T. (2008). Perceptual adaptation to non-native speech.
Cognition 106, 707–729. doi: 10.1016/j.cognition.2007.04.005
Bricker, P. D., and Pruzansky, S. (1976). “Speaker recognition,” in Contemporary
Issues in Experimental Phonetics, ed. N. J. Lass (New York: Academic), 295–326.
www.frontiersin.org January 2015 |Volume 5 |Article 1543 |9
Kriengwatana et al. Revisiting vocal perception in animals
Brown, C. J. (1979). Reactions of infants to their parents’ voices. Infant Behav. Dev.
2, 295–300. doi: 10.1016/S0163-6383(79)80038-7
Burdick, C. K., and Miller, J. D. (1975). Speech perception by the chinchilla:
discrimination of sustained /a/ and /i/. J. Acoust. Soc. Am. 58, 415–427. doi:
10.1121/1.380686
Candiotti, A., Zuberbühler, K., and Lemasson, A. (2013). Voice discrimination in
four primates. Behav. Process. 99, 67–72. doi: 10.1016/j.beproc.2013.06.010
Carbonell, K. M., and Lotto, A. J. (2014). Speech is not special... again. Front.
Psychol. 5:427. doi: 10.3389/fpsyg.2014.00427
Chew, S. J., Vicario, D. S., and Nottebohm, F. (1996). A large-capacity memory
system that recognizes the calls and songs of individual birds. Proc. Natl. Acad.
Sci. U.S.A. 93, 1950–1955. doi: 10.1073/pnas.93.5.1950
Clarke, C. M., and Garrett, M. F. (2004). Rapid adaptation to foreign-accented
English. J. Acoust. Soc. Am. 116, 3647–3658. doi: 10.1121/1.1815131
Creel, S. C., and Bregman, M. R. (2011). How Talker Identity Relates to
Language Processing. Lang. Lingist. Compass 5, 190–204. doi: 10.1111/j.1749-
818X.2011.00276.x
Cristia, A., Seidl, A., Vaughn, C., Schmale, R., Bradlow, A., and Floccia, C. (2012).
Linguistic processing of accented speech across the lifespan. Front. Psychol. 3:479.
doi: 10.3389/fpsyg.2012.00479
Cusack, R., and Carlyon, R. P. (2003). Perceptual asymetries in audition. J. Exp.
Psychol. Hum. Percept. Perform. 29, 713–725. doi: 10.1037/0096-1523.29.
3.713
DeCasper, A. J., and Fifer, W. P. (1980). Of human bonding: newborns prefer their
mother’s voices. Science 208, 1174–1176. doi: 10.1126/science.7375928
DeCasper, A. J., and Prescott, P. A. (1984). Human newborns’ perception of male
voices: preference, discrimination, and reinforcing value. Dev. Psychobiol. 17,
481–91. doi: 10.1002/dev.420170506
Dehaene-Lambertz, G., Montavont, A., Jobert, A., Allirol, L., Dubois, J., Hertz-
Pannier, L., et al. (2010). Language or music, mother or Mozart? structural and
environmental influences on infants’ language networks. Brain Lang. 114, 53–65.
doi: 10.1016/j.bandl.2009.09.003
Dejardins, R. N., and Trainor, L. J. (1998). Fundamental frequency influences vowel
discrimination in 6-month-old infants. Can. Acoust. Proc. 26, 96–97.
Dewson, J. H. (1964). Speech sound discrimination by cats. Science 144, 555–556.
doi: 10.1126/science.144.3618.555
Dewson, J. H., Pribram, K. H., and Lynch, J. C. (1969). Effects of ablations of
temporal cortex upon speech sound discrimination in the monkey. Exp. Neurol.
24, 579–591. doi: 10.1016/0014-4886(69)90159-9
Diehl, R. L., Lotto, A. J., and Holt, L. L. (2004). Speech perception. Annu. Rev.
Psychol. 55, 149–79. doi: 10.1146/annurev.psych.55.090902.142028
Dooling, R. J., Best, C. T., and Brown, S. D. (1995). Discrimination of synthetic full-
formant and sinewave /ra-la/ continua by Budgerigars (Melopsittacus undulatus)
and Zebra finches (Taeniopygia guttata). J. Acoust. Soc. Am. 97, 1839–1846. doi:
10.1121/1.412058
Dooling, R. J., and Brown, S. D. (1990). Speech perception by budgerigars
(Melopsittacus undulatus): spoken vowels. Percept. Psychophys. 47, 568–574. doi:
10.3758/BF03203109
Engineer, C. T., Perez, C. A., Carraway, R. S., Chang, K. Q., Roland, J. L., Sloan,
A. M., and Kilgard, M. P. (2013). Similarity of cortical activity patterns pre-
dicts generalization behavior. PLoS ONE 8:e78607. doi: 10.1371/journal.pone.
0078607
Eriksson, J. L., and Villa, A. E. P. (2006). Learning of auditory equivalence classes for
vowels by rats. Behav. Process. 73, 348–59. doi: 10.1016/j.beproc.2006.08.005
Escudero, P., and Bion, R. (2007). “Modeling vowel normalization and sound per-
ception as sequential processes,” in Proceedings of the 16th International Congress
of Phonetic Sciences, Saarbrücken, 1413–1416.
Fellowes, J. M.,Remez, R. E., and Rubin, P. E. (1997). Perceiving the sex and identity
of a talker without natural vocal timbre. Percept. Psychophys. 59, 839–849. doi:
10.3758/BF03205502
Ficken, M. S., Ficken, R. W., and Witkin, S. R. (1978). Vocal repertoire of the
black-capped chickadee. Auk 95, 34–48.
Fitch, W. T. (1997). Vocal tract length and formant frequency dispersion correlate
with body size in rhesus macaques. J. Acoust. Soc. Am. 102, 1213–1222. doi:
10.1121/1.421048
Fitch, W. T. (1999). Acoustic exaggeration of size in birds by tracheal elongation:
comparative and theoretical analyses. J. Zool. 248, 31–49. doi: 10.1111/j.1469-
7998.1999.tb01020.x
Flege, J. M. (1984). The detection of French accent by American listeners. J. Acoust.
Soc. Am. 76, 692–707. doi: 10.1121/1.391256
Formisano, E., De Martino, F., Bonte, M., and Goebel, R. (2008). “Who” is saying
“What”? Brain-based decoding of human voice and speech. Science 322, 970–973.
doi: 10.1126/science.1164318
Friendly, R. H., Rendall, D., and Trainor, L. J. (2014). Learning to differentiate
individuals by their voices: infants’ individuation of native- and foreign-species
voices. Dev. Psychobiol. 56, 228–37. doi: 10.1002/dev.21164
Fujisaki, H., and Kawashima,T. (1968). The roles of pitch and higher formants in the
perception of vowels. IEEE T. Speech. 16, 73–77. doi: 10.1109/TAU.1968.1161952
Fukuzawa, M., Mills, D. S., and Cooper, J. J. (2005). The effect of
human command phonetic characteristics on auditory cognition in dogs
(Canis familiaris). J. Comp. Psychol. 119, 117–120. doi: 10.1037/0735-7036.
119.1.117
Galeotti, P., Saino, N., Sacchi, R., and Møller,A. P. (1997). Song correlates with social
context, testosteroneand body condition in male barn swallows. Anim. Behav. 53,
687–700. doi: 10.1006/anbe.1996.0304
Gebhart, A. L., Newport, E. L., and Aslin, R. N. (2009). Statistical learning of adjacent
and non-adjacent dependencies among non-linguistic sounds. Psychon. Bull. Rev.
16, 486–490. doi: 10.3758/PBR.16.3.486
Gentner, T. Q., and Hulse,S. H. (1998). Perceptual mechanisms for individual vocal
recognition in European starlings, Sturnus vulgaris.Anim. Behav. 56, 579–594.
doi: 10.1006/anbe.1998.0810
Gentner, T. Q., Hulse, S. H., Bentley, G. E., and Ball, G. F. (2000). Individual
vocal recognition and the effect of partial lesions to HVc on discrimina-
tion, learning, and categorization of conspecific song in adult songbirds.
J. Neurobiol. 42, 117–133. doi: 10.1002/(SICI)1097-4695(200001)42:1<117::AID-
NEU11>3.0.CO;2-M
Ghazanfar, A. A., Neuhoff, J. G., and Logothetis, N. K. (2002). Auditory looming
perception in rhesus monkeys. Proc. Natl. Acad. Sci. U.S.A. 99, 15755–15757. doi:
10.1073/pnas.242469699
Godard, R. (1991). Long-term memory of individual neighbours in a migratory
songbird. Nature 350, 228–229. doi: 10.1038/350228a0
Godard, R., and Wiley, R. H. (1995). Individual recognition of song repertoires
in two wood warblers. Behav. Ecol. Sociobiol. 3, 119–123. doi: 10.1007/BF001
64157
Griebel, U., and Oller, D. K. (2012). Vocabulary learning in a Yorkshire terrier:
slow mapping of spoken words. PLoS ONE 7:e30182. doi: 10.1371/jour-
nal.pone.0030182
Grossmann, T., Oberecker, R., Koch,S. P., and Friederici, A. D. (2010). The develop-
mental origins of voice processing in the human brain. Neuron 65, 852–858. doi:
10.1016/j.neuron.2010.03.001
Growcott, A., Miller, B., Sirguey, P., Slooten, E., and Dawson, S. (2011). Measuring
body length of male sperm whales from their clicks: the relationship between
inter-pulse intervals and photogrammetrically measured lengths. J. Acoust. Soc.
Am. 130, 68–73. doi: 10.1121/1.3578455
Hailman, J. P., Ficken, M. S., and Ficken, R. W. (1985). The ‘chick-a-dee’ calls of
Parus atricapillus: a recombinant system of animal communication compared
with written english. Semiotica 56, 191–224. doi: 10.1515/semi.1985.56.3-4.191
Hartman, D. E. (1979). The perceptual identity and characteristics of aging in
normal male adult speakers. J. Commun. Disord. 12, 53–61. doi: 10.1016/0021-
9924(79)90021-2
Hepper, P., Scott, D., and Shahidullah, S. (1993). Newborn and fetal
response to maternal voice. J. Reprod. Infant Psychol. 11, 147–153. doi:
10.1080/02646839308403210
Hienz, R. D., Aleszczyk, C. M., and May, B. J. (1996). Vowel discrimination in cats:
acquisition, effects of stimulus level, and performance in noise. J. Acoust. Soc. Am.
99, 3656–3668. doi: 10.1121/1.414980
Hienz, R. D., Sachs, M. B., and Sinnott, J. M. (1981). Discrimination of steady-
state vowels by blackbirds and pigeons. J. Acoust. Soc. Am. 70, 699–706. doi:
10.1121/1.386933
Hillenbrand, J., Getty, L. A., Clark, M. J., and Wheeler, K. (1995). Acoustic char-
acteristics of American english vowels. J. Acoust. Soc. Am. 97, 3099–3111. doi:
10.1121/1.411872
Holekamp, K., Boydston, E., Szykman, M., Graham, I., Nutt, K., Birch, S.,
et al. (1999). Vocal recognition in the spotted hyena and its possible implica-
tions regarding the evolution of intelligence. Anim. Behav. 58, 383–395. doi:
10.1006/anbe.1999.1157
Frontiers in Psychology |Language Sciences January 2015 |Volume 5 |Article 1543 |10
Kriengwatana et al. Revisiting vocal perception in animals
Holt, L. L., Lotto, A. J., and Kluender, K. R. (1998). Incorporating principles of
general learning in theories of language acquisition. Chicago Linguist. Soc. 34,
253–268.
Houston, D. M., and Jusczyk, P. W. (2000). The role of talker-specific information
in word segmentation by infants. J. Exp. Psychol. Hum. Percept. Perform. 26,
1570–1582. doi: 10.1037/0096-1523.26.5.1570
Houston-Price, C., and Nakai, S. (2004). Distinguishing novelty and familiar-
ity effects in infant preference procedures. Infant Child Dev. 13, 341–348. doi:
10.1002/icd.364
Illmann, G., Schrader, L., Spinka, M., and Sustr, P. (2002). Acoustical mother-
offspring recognition in pigs (Sus scrofa domestica). Behaviour 139, 487–505. doi:
10.1163/15685390260135970
Imaizumi, S., Mori, K., Kiritani, S., Kawashima, R., Sugiura, M., Fukuda, H.,
et al. (1997). Vocal identification of speaker and emotion activates different brain
regions. Neuroreport 8, 2809–2812. doi: 10.1097/00001756-199708180-00031
Irino, T., and Patterson, R. D. (1996). Temporal asymmetry in the auditory system.
J. Acoust. Soc. Am. 99, 2316–2331. doi: 10.1121/1.415419
Janik, V. M., Sayigh, L. S., and Wells, R. S. (2006). Signature whistle shape conveys
identity information to bottlenose dolphins. Proc. Natl. Acad. Sci. U.S.A. 103,
8293–8297. doi: 10.1073/pnas.0509918103
Johnson, E. K., Westrek, E., Nazzi, T., and Cutler, A. (2011). Infant ability to
tell voices apart rests on language experience. Dev. Sci. 14, 1002–1011. doi:
10.1111/j.1467-7687.2011.01052.x
Johnson, K. (1990). The role of perceived speaker identity in F0 normalization of
vowels. J. Acoust. Soc. Am. 88, 642–654. doi: 10.1121/1.399767
Johnson, K. (2005). “Speaker normalization in speech perception,”in Handbook of
Speech Perception, eds D. B. Pisoni and R. E. Remez (Oxford: Blackwell), 363–389.
doi: 10.1002/9780470757024.ch15
Johnson, K., Strand, E. A., and D’Imperio, M. (1999). Auditory–visual inte-
gration of talker gender in vowel perception. J. Phon. 27, 359–384. doi:
10.1006/jpho.1999.0100
Jouventin, P., and Aubin, T. (2002). Acoustic systems are adapted to breeding ecolo-
gies: individual recognition in nesting penguins. Anim. Behav. 64, 747–757. doi:
10.1006/anbe.2002.4002
Jouventin, P., Aubin, T.,and Lengagne, T. (1999). Finding a parent in a king penguin
colony: the acoustic system of individual recognition. Anim. Behav. 57, 1175–
1183. doi: 10.1006/anbe.1999.1086
Jusczyk, P. W., and Luce, P. A. (2002). Speech perception and spoken word
recognition: past and present. Ear Hear. 23, 2–40. doi: 10.1097/00003446-
200202000-00002
Jusczyk, P. W., Pisoni, D. B., and Mullennix, J. (1992). Some consequences of
stimulus variability on speech processing by 2-month-old infants. Cognition 43,
253–291. doi: 10.1016/0010-0277(92)90014-9
Kaminski, J., Call, J., and Fischer, J. (2004). Word learning in a domestic dog:
evidence for “fast mapping”. Science 304, 1682–1683. doi: 10.1126/science.
1097859
Kisilevsky, B. S., Hains, S. M. J., Brown, C. A., Lee, C. T., Cowperthwaite,
B., Stutzman, S. S., et al. (2009). Fetal sensitivity to properties of maternal
speech and language. Infant Behav. Dev. 32, 59–71. doi: 10.1016/j.infbeh.2008.
10.002
Kisilevsky, B. S., Hains, S. M. J., Lee, K., Xie, X., Huang, H., Ye, H. H., et al. (2003).
Effects of experience on fetal voice recognition. Psychol. Sci. 14, 220–224. doi:
10.1111/1467-9280.02435
Kluender, K. R., Diehl, R. L., and Killeen, P. R. (1987). Japanese quail can learn
phonetic categories. Science 237, 1195–1197. doi: 10.1126/science.3629235
Kluender, K. R., Lotto, A. J., and Holt, L. L. (2005). “Contributions of nonhuman
animal models to understanding human speech perception,”in Listening to Speech:
An Auditory Perspective, eds S. Greenberg and W. Ainsworth (New York, NY:
Oxford University Press),203–220.
Kojima, S., and Kiritani, S. (1989). Vocal-auditory functions in the chim-
panzee: vowel perception. Int. J. Primatol. 10, 199–213. doi: 10.1007/
BF02735200
Kreiman, J., Gerratt, B. R., Precoda, K., and Berke, G. S. (1992). Individual dif-
ferences in voice quality perception. J. Speech Hear. Res. 35, 512–520. doi:
10.1044/jshr.3503.512
Kuhl, P. K. (1981). Discrimination of speech by nonhuman animals: basic auditory
sensitivities conducive to the perception of speech-sound categories. J. Acoust.
Soc. Am. 70, 340–349. doi: 10.1121/1.386782
Kuhl, P. K. (1983). Perception of auditory equivalence classes for speech in early
infancy. Infant Behav. Dev. 6, 263–285. doi: 10.1016/S0163-6383(83)80036-8
Kuhl, P. K., and Miller, J. D. (1975). Speech perception by the chinchilla: voiced-
voiceless distinction in alveolar plosive consonants. Science 190, 69–72. doi:
10.1126/science.1166301
Ladefoged, P., and Broadbent, D. (1957). Information conveyed by vowels. J. Acoust.
Soc. Am. 29, 98–104. doi: 10.1121/1.1908694
Lampe, J. F., and Andre, J. (2012). Cross-modal recognition of human individuals in
domestic horses (Equus caballus). Anim. Cogn. 15, 623–630. doi: 10.1007/s10071-
012-0490-1
Latinus, M., and Belin, P. (2011). Human voice perception. Curr. Biol. 21, R143–
R145. doi: 10.1016/j.cub.2010.12.033
Lavner,Y., Gath, I., and Rosenhouse, J. (2000). The effects of acoustic modifications
on the identification of familiar voices speaking isolated vowels. Speech Commun.
30, 9–26. doi: 10.1016/S0167-6393(99)00028-X
Leaver,A. M., and Rauschecker, J. P. (2010). Cortical representation of natural com-
plex sounds: effects of acoustic features and auditory object category. J. Neurosci.
30, 7604–7612. doi: 10.1523/jneurosci.0296-10.2010
Lee, G. Y., and Kisilevsky, B. S. (2014). Fetuses respond to father’s voice but
prefer mother’s voice after birth. Dev. Psychobiol. 56, 1–11. doi: 10.1002/dev.
21084
Lee, W. Y., Lee, S., Choe, J. C., and Jablonski, P. G. (2011). Wild birds recognize
individual humans: experiments on magpies, Pica pica. Anim. Cogn. 14, 817–825.
doi: 10.1007/s10071-011-0415-4
Levey, D. J., London, G. A., Poulsen, J. R., Stracey, C. M., and Robinson, S. K. (2009).
Urban mockingbirds quickly learn to identify. Proc. Natl. Acad. Sci. U.S.A. 106,
8959–8962. doi: 10.1073/pnas.0811422106
Lotto, A. J., Kluender, K. R., and Holt, L. L. (1997a). Perceptual Compensation for
coarticulation by Japanese quail (Coturnix coturnix japonica). J. Acoust. Soc. Am.
102, 1134–1140. doi: 10.1121/1.419865
Lotto, A. J., Kluender, K. R., and Holt, L. L. (1997b). Animal models of speech
perception phenomena. Chicago Linguist. Soc. 33, 357–367.
Magnuson, J. S., and Nusbaum, H. C. (2007). Acoustic differences, listener expec-
tations, and the perceptual accommodation of talker variability. J. Exp. Psychol.
Hum. Percept. Perform. 33, 391–409. doi: 10.1037/0096-1523.33.2.391
Mammen, D. L., and Nowicki, S. (1981). Individual differences and within-
flock convergence in Chickadee Calls.Behav. Ecol. Sociobiol. 9, 179–186. doi:
10.1007/BF00302935
Marzluff, J. M., Miyaoka, R., Minoshima, S., and Cross, D. J. (2012). Brain
imaging reveals neuronal circuitry underlying the crow’s perception of human
faces. Proc. Natl. Acad. Sci. U.S.A. 109, 15912–15917. doi: 10.1073/pnas.120
6109109
Marzluff, J. M., Walls, J., Cornell, H. N., Withey, J. C., and Craig, D. P. (2010).
Lasting recognition of threatening people by wild American crows. Anim. Behav.
79, 699–707. doi: 10.1016/j.anbehav.2009.12.022
Maye, J., Werker, J. F., and Gerken, L. (2002). Infant sensitivity to distributional
information can affect phonetic discrimination. Cognition 82, B101–B111. doi:
10.1016/S0010-0277(01)00157-3
McComb, K., Moss, C., Sayialel, S., and Baker, L. (2000). Unusually extensive
networks of vocal recognition in African elephants. Anim. Behav. 59, 1103–1109.
doi: 10.1006/anbe.2000.1406
McComb, K., Shannon, G., Sayialel, K. N., and Moss, C. (2014). Elephants can
determine ethnicity, gender, and age from acoustic cues in human voices. Proc.
Natl. Acad. Sci. U.S.A. 111, 5433–5438. doi: 10.1073/pnas.1321543111
Miller, J. D. (1989). Auditory-perceptual interpretation of the vowel. J. Acoust. Soc.
Am. 85, 2114–2134. doi: 10.1121/1.397862
Mills, D. S. (2005). What’s in a word? a review of the attributes of a com-
mand affecting the performance of pet dogs. Anthrozoös 18, 208–221. doi:
10.2752/089279305785594108
Monahan, P. J., and Idsardi, W. J. (2010). Auditory Sensitivity to Formant Ratios:
Toward an Account of Vowel Normalization. Lang. Cogn. Process. 25, 808–839.
doi: 10.1080/01690965.2010.490047
Mullennix, J. W., Johnson, K. A., Topcu-Durgun, M., and Farnsworth, L. M. (1995).
The perceptual representation of voice gender. J. Acoust. Soc. Am. 98, 3080–3095.
doi: 10. 1121/1.413832
Mullennix, J. W., Pisoni, D. B., and Martin, C. S. (1989). Some effects of talker
variability on spoken word recognition. J. Acoust. Soc. Am. 85, 365–378. doi:
10.1121/1.397688
www.frontiersin.org January 2015 |Volume 5 |Article 1543 |11
Kriengwatana et al. Revisiting vocal perception in animals
Nakamura, K., Kawashima, R., Sugiura, M., Nakamura, A., Hatano, K., Nagumo,
S., et al. (2001). Neural substrates for recognition of familiar voices: a PET study.
Neuropsychologia 39, 1047–1054. doi: 10.1016/S0028-3932(01)00037-9
Naoi, N., Watanabe, S., Maekawa, K., and Hibiya, J. (2012). Prosody discrimi-
nation by songbirds (Padda oryzivora). PLoS ONE 7:e47446. doi: 10.1371/jour-
nal.pone.0047446
Nearey,T. M. (1989). Static, dynamic, and relational properties in vowel perception.
J. Acoust. Soc. Am. 85, 2088–2113. doi: 10.1121/1.397861
Neuhoff, J. G. (1998). Perceptual bias for rising tones. Nature 395, 123–124. doi:
10.1038/25862
Nowicki, S. (1989). Vocal plasticity in captive black-capped chickadees: the acoustic
basis and rate of call convergence. Anim. Behav. 38, 64–73. doi: 10.1016/0003-
3472(89)90007-9
Nygaard, L. C., and Pisoni, D. B. (1998). Talker-specific learning in
speech perception. Percept. Psychophys. 60, 355–376. doi: 10.3758/
BF03206860
Ohms, V. R., Escudero, P., Lammers, K., and ten Cate, C. (2012). Zebra finches
and Dutch adults exhibit the same cue weighting bias in vowel perception. Anim.
Cogn. 15, 155–61. doi: 10.1007/s10071-011-0441-2
Ohms, V. R., Gill, A., Van Heijningen, C. A. A., Beckers, G. J. L., and ten
Cate, C. (2010). Zebra finches exhibit speaker-independent phonetic percep-
tion of human speech. Proc. R. Soc. Lond. B Biol. Sci. 277, 1003–1009. doi:
10.1098/rspb.2009.1788
Otter, K., Mcgregor, P. K., Terry, A. M. R., Burford, F. R. L., Peake, T. M., and Dabel-
steen, T. (1999). Do female great tits (Parus major) assess males by eavesdropping?
A field study using interactive song playback. Proc. R. Soc. Lond. B Biol. Sci. 266,
1305–1309. doi: 10.1098/rspb.1999.0779
Owren, M. J., Hopp, S. L., Sinnott, J. M., and Petersen, M. R. (1988). Absolute
auditory thresholds in three old world monkey species (Cercopithecus aethiops,
C. neglectus, Macaca fuscata) and humans (Homo sapiens). J. Comp. Psychol. 102,
99–107. doi: 10.1037/0735-7036.102.2.99
Parejo, D., and Avilés, J. M. (2007). Do avian brood parasites eavesdrop on het-
erospecific sexual signals revealing host quality? a review of the evidence. Anim.
Cogn. 10, 81–88. doi: 10.1007/s10071-006-0055-2
Pelucchi, B., Hay, J. F., and Saffran, J. R. (2009). Statistical learning in a natural
language by 8-month-old infants. Child Dev. 80, 674–85. doi: 10.1111/j.1467-
8624.2009.01290.x
Perez, E. C., Elie, J. E., Soulage, C. O., Soula, H. A., Mathevon, N., and Vignal, C.
(2012). The acoustic expression of stress in a songbird: does corticosterone drive
isolation-induced modifications of zebra finch calls? Horm. B ehav. 61, 573–581.
doi: 10.1016/j.yhbeh.2012.02.004
Peterson, G. E., and Barney, H. H. (1952). Control methods used in a study of the
vowels. J. Acoust. Soc. Am. 24, 175–184. doi: 10.1121/1.1906875
Polka, L., and Bohn,O. S. (1996). A cross-language comparison of vowel perception
in English-learning and German-learning infants. J. Acoust. Soc. Am. 100, 577–
592. doi: 10.1121/1.415884
Polka, L., and Bohn, O.-S. (2003). Asymmetries in vowel perception. Speech
Commun. 41, 221–231. doi: 10.1016/S0167-6393(02)00105-X
Polka, L., and Bohn, O.-S. (2011). Natural referent vowel (NRV) framework:
an emerging view of early phonetic development. J. Phon. 39, 467–478. doi:
10.1016/j.wocn.2010.08.007
Pons, F. (2006). The effects of distributional learning on rats’ sensitivity to phonetic
information. J. Exp. Psychol. Anim. Behav. Process. 32, 97–101. doi: 10.1037/0097-
7403.32.1.97
Potter, R. K., and Steinberg, J. C. (1950). Toward the specification of speech. J. Acoust.
Soc. Am. 22, 807–820. doi: 10.1121/1.1906694
Proops, L., and McComb, K. (2012). Cross-modal individual recognition in domes-
tic horses (Equus caballus) extends to familiar humans. Proc. R. Soc. Lond. B Biol.
Sci. 279, 3131–3138. doi: 10.1098/rspb.2012.0626
Rainey, H. J., Zuberbühler, K., and Slater, P. J. B. (2004). Hornbills can distinguish
between primate alarm calls. Proc. R. Soc. Lond. B Biol. Sci. 271, 755–759. doi:
10.1098/rspb.2003.2619
Ramos, D., and Ades, C. (2012). Two-item sentence comprehension by a
dog (Canis familiaris). PLoS ONE 7:e29689. doi: 10.1371/journal.pone.00
29689
Ramus, F., Raspail, B., Hauser, M. D., Miller, C., and Morris, D. (2000). Language
discrimination by human newborns and by cotton-top tamarin monkeys. Science
288, 349–351. doi: 10.1126/science.288.5464.349
Ratcliffe, V. F., McComb, K., and Reby, D. (2014). Cross-modal discrimina-
tion of human gender by domestic dogs. Anim. Behav. 91, 127–135. doi:
10.1016/j.anbehav.2014.03.009
Remez, R. E., Rubin, P. E., Nygaard, L. C., and Howell, W. A. (1987). Perceptual
normalization of vowels produced by sinusoidal voices. J. Exp. Psychol. Hum.
Percept. Perform. 13, 40–61. doi: 10.1037/0096-1523.13.1.40
Rendall, D., Rodman, P. S., and Emond, R. E. (1996). Vocal recognition of individ-
uals and kin in free-ranging rhesus monkeys. Anim. Behav. 51, 1007–1015. doi:
10.1006/anbe.1996.0103
Saffran, J. R., Aslin, R. N., and Newport, E. L. (1996). Statistical learning by 8-
month-old infants. Science 274, 1926–1928. doi: 10.1126/science.274.5294.1926
Saffran, J. R., Johnson, E. K., Aslin, R. N., and Newport, E. L. (1999). Statistical
learning of tone sequences by human infants and adults. Cognition 70, 27–52.
doi: 10.1016/S0010-0277(98)00075-4
Saito, A., and Shinozuka, K. (2013). Vocal recognition of owners by domestic cats
(Felis catus). Anim. Cogn. 16, 685–690. doi: 10.1007/s10071-013-0620-4
Samuel, A. G. (2011). Speech perception. Annu.Rev.Psychol.62, 49–72. doi:
10.1146/annurev.psych.121208.131643
Samuel, A. G., and Kraljic, T. (2009). Perceptual learning for speech. Atten. Percept.
Psychophys. 71, 1207–1218. doi: 10.3758/APP.71.6.1207
Schlauch, R. S., Ries, D. T., and DiGiovanni, J. J. (2001). Duration discrimination
and subjective duration for ramped and damped sounds. J. Acoust. Soc. Am. 109,
2880–2887. doi: 10.1121/1.1372913
Schultz, S., Vouloumanos, A., Bennett, R. H., and Pelphrey, K. (2014). Neural
specialization for speech in the first months of life. Dev. Sci. 17, 766–774. doi:
10.1111/desc.12151
Seppänen, J. T., Forsman, J. T., Mönkkönen, M., and Thomson, R. L. (2007).
Social information use is a process across time, space, and ecology, reaching
heterospecifics. Ecology 88, 1622–1633. doi: 10.1890/06-1757.1
Sharp, S. P., McGowan, A., Wood, M. J., and Hatchwell, B. J. (2005). Learned
kin recognition cues in a social bird. Nature 434, 1127–30. doi: 10.1038/nature
03522
Sinnott, J. M. (1989). Detection and discrimination of synthetic English vowels by
Old World monkeys (Cercopithecus, Macaca) and humans. J. Soc. Acoust. Am. 86,
557–565. doi: 10.1121/1.398235
Sinnott, J. M., and Aslin, R. N. (1985). Frequency and intensity discrimina-
tion in human infants and adults. J. Acoust. Soc. Am. 78, 1986–1992. doi:
10.1121/1.392655
Sinnott, J. M., Petersen, R., and Hopp, S. L. (1985). Frequency and intensity dis-
crimination in humans and monkeys. J. Acoust. Soc. Am. 78, 1977–1985. doi:
10.1121/1.392654
Sliwa, J., Duhamel, J.-R., Pascalis, O., and Wirth, S. (2011). Spontaneous
voice-face identity matching by rhesus monkeys for familiar conspecifics and
humans. Proc. Natl. Acad. Sci. U.S.A. 108, 1735–1740. doi: 10.1073/pnas.10081
69108
Smith, D. R. R. (2014). Does knowing speaker sex facilitate vowel recognition at
short durations? Acta Psychol. 148, 81–90. doi: 10.1016/j.actpsy.2014.01.010
Soma, K. K., Wissman, A. M., Brenowitz, E. A., and Wingfield, J. C. (2002).
Dehydroepiandrosterone (DHEA) increases territorial song and the size of an
associated brain region in a male songbird. Hor m. Behav. 41, 203–212. doi:
10.1006/hbeh.2001.1750
Spierings, M. J., and ten Cate, C. (2014). Zebra finches are sensitive to prosodic
features of human speech. Proc. R. Soc. Lond. B Biol. Sci. 281:20140480. doi:
10.1098/rspb.2014.0480
Strange, W., Jenkins, J. J., and Johnson, T. L. (1983). Dynamic specification of
coarticulated vowels. J. Acoust. Soc. Am. 74, 695–705. doi: 10.1121/1.389855
Strange, W.,Verbrugge, R. R., Shankweiler, D. P., and Edman, T. R. (1976). Conso-
nant environment specifies vowel identity. J. Acoust. Soc. Am. 60, 213–224. doi:
10.1121/1.381066
Story, B. H., and Titze, I. R. (2002). A preliminary study of voice quality transfor-
mation based on modifications to the neutral vocal tract area function. J. Phon.
30, 485–509. doi: 10.1006/jpho.2002.0168
Swoboda, P. J., Kass, J., Morse, P. A., and Leavitt, L. A. (1978). Memory factors in
infant vowel discrimination of normal and at-risk infants. Child Dev. 49, 332–339.
doi: 10.2307/1128695
Syrdal, A. K., and Gopal, H. S. (1986). A perceptual model of vowel recognition
based on the auditory representation of American English vowels. J. Acoust. Soc.
Am. 79, 1086–1100. doi: 10.1121/1.393381
Frontiers in Psychology |Language Sciences January 2015 |Volume 5 |Article 1543 |12
Kriengwatana et al. Revisiting vocal perception in animals
Templeton, C. N., and Greene, E. (2007). Nuthatches eavesdrop on variations in
heterospecific chickadee mobbing alarm calls. Proc. Natl. Acad. Sci. U.S.A. 104,
5479–5482. doi: 10.1073/pnas.0605183104
Templeton, C. N., Greene, E., and Davis, K. (2005). Allometry of alarm calls:
black-capped chickadees encode information about predator size. Science 308,
1934–1937. doi: 10.1126/science.1108841
ten Cate, C. (2014). On the phonetic and syntactic processing abilities of birds: From
songs to speech and artificial grammars. Curr. Opin. Neurobiol. 28, 157–164 doi:
10.1016/j.conb.2014.07.019
Tibbetts, E. A., and Dale,J. (2007). Individual recognition: it is good to be different.
Trends Ecol. Evol. 22, 529–37. doi: 10.1016/j.tree.2007.09.001
Toro, J. M., Trobalon, J. B., and Sebastián-Gallés, N. (2003). The use of prosodic
cues in language discrimination tasks by rats. Anim. Cogn. 6, 131–136. doi:
10.1007/s10071-003-0172-0
Trout, J. D. (2001). The biological basis of speech: what to infer from talking to the
animals. Psychol. Rev. 108, 523–549. doi: 10.1037/0033-295X.108.3.523
Trude, A. M., and Brown-Schmidt, S. (2012). Talker-specific perceptual adapta-
tion during online speech perception. Lang. Cogn. Process. 27, 979–1001. doi:
10.1080/01690965.2011.597153
Tuomainen, J., Savela, J., Obleser, J., and Aaltonen, O. (2013). Attention modulates
the use of spectral attributes in vowel discrimination: behavioral and event-related
potential evidence. Brain Res. 1490, 170–183. doi: 10.1016/j.brainres.2012.10.067
van Heugten, M., and Johnson, E. K. (2014). Learning to contend with accents in
infancy: benefits of brief speaker exposure. J. Exp. Psychol. Gen. 143, 340–350.
doi: 10.1037/a0032192
von Kriegstein, K., Eger, E., Kleinschmidt,A., and Giraud, A. L. (2003). Modulation
of neural responses to speech by directing attention to voices or verbal content.
Brain Res. Cogn. Brain Res. 17, 48–55. doi: 10.1016/S0926-6410(03)00079-X
von Kriegstein, K., Warren, J. D., Ives, D. T., Patterson, R. D., and Griffiths, T. D.
(2006). Processing the acoustic effect of size in speech sounds. NeuroImage 32,
368–375. doi: 10.1016/j.neuroimage.2006.02.045
Vouloumanos, A., Hauser, M. D., Werker, J. F., and Martin, A. (2010). The tun-
ing of human neonates’ preference for speech. Child Dev. 81, 517–27. doi:
10.1111/j.1467-8624.2009.01412.x
Wakita,H. (1977). Normalization of vowels by vocal-tract length and its application
to vowel identification. IEEE Trans. Acoustic Speech. Signal Process 25, 183–192.
doi: 10.1109/TASSP.1977.1162929
Wanrooij, K., Boersma, P., and van Zuijen, T. L. (2014). Fast phonetic learning
occurs already in 2-to-3-month old infants: an ERP study. Front. Psychol. 5:77.
doi: 10.3389/fpsyg.2014.00077
Warden, C. J., and Warner, L. H. (1928). The sensory capacities and intelligence of
dogs, with a report on the ability of the noted dog “Fellow” to respond to verbal
stimuli. Q. Rev. Biol. 3, 1–28. doi: 10.1086/394292
Warfield, D., Ruben, R. J., and Glackin, R. (1966). Word discrimination in cats.
J. Aud. Res. 6, 97–120.
Wascher, C. A. F., Szipl, G., Boeckle, M., and Wilkinson, A. (2012). You
sound familiar: carrion crows can differentiate between the calls of known and
unknown heterospecifics. Anim. Cogn. 15, 1015–1019. doi: 10.1007/s10071-
012-0508-8
Weary, D. M. (1990). Categorization of song notes in great tits: which acoustic
features are used and why? Anim. Behav. 39, 450–457. doi: 10.1016/S0003-
3472(05)80408-7
Weary, D., Falls, J., and McGregor, P. (1990). Song matching and the percep-
tion of song types in great tits, Parus major.Behav. Ecol. 1, 43–47. doi:
10.1093/beheco/1.1.43
Weary, D. M., and Krebs, J. R. (1992). Great tits classify songs by individual voice
characteristics. Anim. Behav. 43, 283–287. doi: 10.1016/S0003-3472(05)80223-4
White, K. S., and Aslin, R. N. (2011). Adaptation to novel accents by toddlers. Dev.
Sci. 14, 372–384. doi: 10.1111/j.1467-7687.2010.00986.x
Zoloth, S. R., Petersen, M. R., Beecher, M. D., Green, S., Marler, P., Moody, D. B.,
et al. (1979). Species-specific perceptual processing of vocal Sounds. Science 204,
870–873. doi: 10.1126/science.108805
Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
Received: 23 September 2014; accepted: 12 December 2014; published online: 13
January 2015.
Citation: Kriengwatana B, Escudero P and ten Cate C (2015) Revisiting vocal perception
in non-human animals: a review of vowel discrimination, speaker voice recognition,
and speaker normalization. Front. Psychol. 5:1543. doi: 10.3389/fpsyg.2014.01543
This article was submitted to Language Sciences, a section of the journal Frontiers in
Psychology.
Copyright © 2015 Kriengwatana, Escudero and ten Cate. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (CC BY).
The use, distribution or reproduction in other forums is permitted, provided the or iginal
author(s) or licensor are credited and that the original publication in this journal is cited,
in accordance with accepted academic practice. No use, distribution or reproduction is
permitted which does not comply with these terms.
www.frontiersin.org January 2015 |Volume 5 |Article 1543 |13
Content uploaded by Buddhamas Pralle Kriengwatana
Author content
All content in this area was uploaded by Buddhamas Pralle Kriengwatana on Jan 13, 2015
Content may be subject to copyright.
