# Nonlinear vocal phenomena affect human perceptions of distress, size and dominance in puppy whines

Mathilde Massenet, Andrey Anikin, Katarzyna Pisanski, Karine Reynaud, Nicolas Mathevon, David Reby

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Mathilde Massenet, Andrey Anikin, Katarzyna Pisanski, Karine Reynaud, Nicolas Mathevon, et al. Nonlinear vocal phenomena affect human perceptions of distress, size and dominance in puppy whines. Proceedings of the Royal Society B: Biological Sciences, 2022, 289 (1973), pp.1-9.
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<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Nonlinear vocal phenomena affect human
perceptions of distress, size and dominance in puppy
whines

Mathilde Massenet¹, Andrey Anikin¹,², Katarzyna Pisanski¹,³, Karine Reynaud⁴,⁵, Nicolas Mathevon¹, David Reby¹

¹ Equipe de Neuro-Ethologie Sensorielle, University of Saint Étienne, CNRS, Inserm, St-Étienne, France

² Division of Cognitive Science, Lund University, 22100, Lund, Sweden

³ CNRS, French National Centre for Scientific Research, Laboratoire de Dynamique du Langage, University of Lyon 2, 69007 Lyon, France

⁴ École Nationale Vétérinaire d'Alfort, EnvA, 94700 Maisons-Alfort, France

⁵ Physiologie de la Reproduction et des Comportements, CNRS, IFCE, INRAE, Université de Tours, PRC, Nouzilly, France

ORCIDS: M.M. 0000-0002-0085-1871; A.A. 0000-0002-1250-8261; K.P. 0000-0003-0992-2477; K.R. 0000-0002-8897-6790; N.M. 0000-0003-0219-6601; D.R. 0000-0001-9261-1711

Abstract

While nonlinear phenomena are widely reported in animal vocalisations, often causing perceptual harshness and roughness, their communicative function remains debated.

Several hypotheses have been put forward: attention grabbing, communication of distress, exaggeration of body size and dominance. Here, we use state-of-the-art sound synthesis to investigate how NLP affect the perception of puppy whines by human listeners. Listeners assessed the distress, size, or dominance conveyed by synthetic puppy whines with manipulated NLP, including frequency jumps, and varying proportions of subharmonics, sidebands, and deterministic chaos. We found that the presence of chaos increased the
30 puppy's perceived level of distress and that this effect held across a range of representative
31 $f_0$ levels. Adding sidebands and subharmonics also increased perceived distress among
32 listeners with extensive caregiving experience with pre-weaned puppies (e.g., breeders,
33 veterinarians). Finally, we found that whines with added chaos, subharmonics, or sidebands
34 were associated with larger and more dominant puppies, although these biases were
35 attenuated in experienced caregivers. Together our results show that nonlinear phenomena
36 in puppy whines can convey rich information to human listeners and may thus be crucial for
37 offspring survival during breeding of a domesticated species.
38

## Keywords

40 Nonlinear vocal phenomena, puppy whines, human perception, interspecific communication, animal communication
41

## Introduction

44 There is now widespread evidence that vertebrate vocal signals communicate both static
45 information (e.g., relatively stable physical and social attributes) and dynamic information
46 (e.g., transient emotional and motivational states) about the animals that produce them
47 [1,2]. Investigating how these signals are emitted, and how mechanisms of vocal production
48 determine their acoustic structure, has enabled researchers to better understand their
49 evolution and functions [2].

50 In mammals, the production of vocalisations is initiated in the larynx by vocal fold vibration
51 [3]. The rate at which the vocal folds vibrate determines a key feature of vocal signals, their
52 fundamental frequency ($f_0$), which is largely responsible for their perceived pitch [3]. While
53 vocal fold vibration is typically regular, perturbations can occur, causing abrupt changes in
54 the tonal structure of acoustic signals [4,5]. This results in acoustic irregularities known as
55 nonlinear phenomena (hereafter NLP), which are widely reported in the vocalisations of
56 terrestrial mammals (e.g., koalas (*Phascolarctos cinereus*): [6]; marmots (*Marmota
57 marmota*): [7]; chimpanzees (*Pan troglodytes*): [8]; meerkats (*Suricata suricatta*): [9]; giant
58 pandas (*Ailuropoda melanoleuca*): [10]; dogs (*Canis lupus familiaris*): [11,12]; North
59 American elk (*Cervus canadensis*): [13]; cows (*Bos taurus*): [14] African elephants (*Loxodonta
60 *Africana*): [15]), including humans (*Homo sapiens*) [16,17]. Generally, the presence of NLP in
61 vocalisations is responsible for perceived harshness, roughness and instability [18].

62 Four main types of NLP in animal vocalisations are frequency jumps, subharmonics,
63 sidebands, and deterministic chaos. *Frequency jumps* correspond to sudden changes in vocal
64 fold vibration [19]. *Subharmonics* can appear when one vocal fold vibrates at a period
65 corresponding to an integer fractional value of the second vocal fold (e.g., 1:2, 2:3) [20],
66 while *sidebands* (resulting from biphonation) are produced by the vibration of two
67 independent sound sources (e.g., vocal folds vibrating at two independent frequencies) [4].

68 Finally, *deterministic chaos* (hereafter chaos) usually occurs when vocal folds vibrate in
69 asynchronous nonperiodic regimes [5]. Because of their ubiquity in mammal calls, a
70 consensus is emerging that NLP are not merely by-products of vocal production but rather
71 function to communicate information about the caller [4,5]. However, it remains unclear
72 what kind of information NLP transmit.

73 It has been suggested that NLP are vocal indicators of high arousal [7,11,15,21] in contexts
74 associated with distress (e.g., during separation from conspecifics or immediate risk of
75 predation) [22]. Specifically, chaos represents the most severe and perceptually harsh form
76 of vocal nonlinearity [18] characterizing the distress vocalisations of several mammal
77 species [10,11,15,21–23], including humans [16,17]. For instance, perceptions of distress
78 increase with the presence of NLP in nonverbal vocalisations of human infants [16] and
79 adults [17]. This has led to the suggestion that a possible biological function of NLP may be
80 to reduce habituation in receivers by making these calls unpredictable and thus difficult to
81 ignore [9,24–26].

82 Aside from NLP, f₀ (perceived as pitch) and formant frequencies (vocal tract resonances that
83 influence perceived timbre) also affect the perceptual quality of vocalisations. In many
84 terrestrial mammals, formants reliably predict inter-individual differences in body size,
85 whereas f₀ is usually a better predictor of dominance status [27]. Indeed, animals in
86 aggressive motivational states commonly produce harsh low-pitched calls [28] to potentially
87 signal and/or exaggerate their size and dominance [2]. These signals can therefore play a
88 key role in determining the outcome of agonistic interactions, for instance during sexual
89 competition or territorial defence [27]. In this context, another hypothesis regarding the
90 potential functions of NLP may be to exaggerate perceived size and dominance [4,5]. Some
91 NLP can indeed lower perceived pitch, enhancing the perceptibility of vocal tract resonances
92 by increasing spectral density, and potentially, may affect perceptions of the vocaliser's size
93 and dominance [4,18]. Together, several hypotheses have thus been put forward regarding
94 the functions of NLP: attention grabbing, communication of distress, and/or size or
95 dominance exaggeration.
96 Previous investigations of the perceptual effects of NLP in nonhuman animal vocalisations
97 have focused on a single type (e.g., chaos in lizards (*Liolaemus chiliensis*): [29]; chaos in
98 marmots: [24]; subharmonics in meerkats: [9]; chaos in red deer (*Cervus elaphus*): [26]).
99 Past studies also typically relied on NLP variation in natural vocal sounds (frogs (*Odoranna
100 tormota*): [30]; meerkats: [9,25]; marmots: [24]; red deer: [26]), and hence, could not
101 control for potentially covarying acoustic parameters (e.g., *f*<sub>o</sub>, intensity). It thus remains
102 crucial to understand the biological function(s) of each type of NLP by testing their
103 independent perceptual effects across different species, call types, and behavioural
104 contexts. Yet, until recently, a major limitation in the experimental study of NLP has been
105 the absence of tools to synthesise naturalistic sounds with controlled levels of NLP.
106 Here, we take advantage of recent advances in parametric sound synthesis, thus far used
107 only on human nonverbal vocalisations [18,31,32], to systematically add NLP to synthetic,
108 yet highly realistic, nonhuman animal vocalisations. More specifically, we applied this
109 method to investigate how the presence and duration of NLP in distress whines, produced
110 by 1- to 9-week-old domestic dog puppies, affect their perception by humans. Whines are
111 high-pitched tonal calls considered to signal distress, typically given by puppies during
112 separation [33] or aggression by their mother [34]. Like adult dog whines [11,12], puppy
113 whines also often contain NLP (see electronic supplementary material), particularly when
114 the dog's emotional arousal increases (personal observation). Although puppies' survival
115 mainly relies on mothers, who intensively breastfeed, groom, and warm them [34], the
116 intervention of human caregivers is sometimes required for breeding in this domesticated
117 species [35]. As such, NLP in whines may be important to attract the attention of the
118 mother, but also of humans, ensuring that puppies receive care. Indeed, the common
119 presence of NLP across vertebrate infant distress calls suggests that these shared vocal
120 features may support the interspecific vocal communication of need to human caregivers
121 [22]. Therefore, to investigate the possible function of NLP as vocal indicators of distress in
122 human-puppy interactions, we performed playback experiments using synthetic puppy
123 whines in which we manipulated the presence, and duration, of NLP (frequency jumps,
subharmonics, sidebands, chaos) across $f_o$ levels (low, medium, high). We predicted that NLP added to whines, particularly chaos, would increase human perceptions of the puppy's distress, and that higher proportions of NLP would enhance these perceptual effects. Moreover, because NLP affect perceptions of size and dominance in synthetic human vocalisations [18,32], we tested whether these perceptual effects generalize to other mammal vocalisations. Indeed, dominance-like behaviours have been described as a trait of individual temperament in dogs [36,37], and can occur during the early development of pre-weaned canids, including puppies (e.g., during play with littermates) [36,38]. We thus predicted that NLP would increase perceived size and dominance. Finally, under the assumption that the interspecific function of infant distress vocal signals may be particularly important in caregiving contexts (e.g., for breeders and veterinarians), we replicated our experiment on a distinct sample of professionals with extensive experience in puppy caregiving to test whether such experience modulates the perceived effects of NLP.

## 138 Materials and Methods

Our experimental protocol included: (1) audio recording natural distressed puppy whines, (2) creating synthetic whine stimuli based on these recordings of natural vocalisations, and (3) online playback experiments in which we respectively tested 200 and 217 human listeners from the general population (Experiments 1 and 2), and 55 listeners selected for their extensive experience in puppy caregiving (Experiment 3). All participants judged the perceived level of distress, body size, and dominance conveyed by each synthesized puppy whine. While the first and third playback experiments tested the perceptual effects of the presence or absence of NLP, the second experiment also tested the perceptual effects of their duration (Table 1).

<table><thead><tr><th></th><th>Playback Experiment 1<br>(N=200) and Experiment 3<br>(N=55)</th><th>Playback Experiment 2 (N=217)</th></tr></thead><tbody><tr><td><strong>Total number of original<br>synthetic prototypes</strong></td><td>20</td><td>40</td></tr></tbody></table>
<table><thead><tr><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td rowspan="3">Manipulations</td><td>Types of NLP</td><td>none, frequency jumps, subharmonics, sidebands, chaos</td><td>none, subharmonics, sidebands, chaos</td></tr><tr><td>Duration of NLP (% of whine duration)</td><td>20-40%*</td><td>50% or 80%</td></tr><tr><td>Levels of f<sub>o</sub></td><td>low, medium, high</td><td>low, medium, high</td></tr><tr><td colspan="2">Total number of synthetic stimuli</td><td>300</td><td>840</td></tr></tbody></table>

Table 1: Overview of the experimental design used for playback experiments. Level of manipulation ‘none’ indicates vocal stimuli without NLP. * Values drawn at random within this range, derived from the peak of the observed distribution of NLP durations.

Experiments 1 and 3 shared an identical design and identical whine stimuli.

Acoustic recordings

We recorded whines of 32 Beagle puppies from 6 different litters at roughly 1-, 3-, 6-, and 9-weeks of age (Table S1) at two different breeding facilities (France). We used a Sennheiser MKH70 directional microphone connected to an audio recorder Zoom H4n (44.1kHz, 24bit) and positioned at approximatively 30 cm from the animal’s mouth.

Mothers and their litter stayed in the same enclosure during the 9 first weeks of the puppies’ lives. To record natural whines, each puppy was placed alone in a pen in a separate room (roughly 100 x 50cm). Each puppy was thus recorded in a separation behavioural context, without visual and acoustic contact with its mother and littermates. This method of recording distress vocalisations has been widely applied in vertebrates [22]. Our recordings started once the puppy had produced its first whine and did not last for more than 5 minutes to limit stress potentially induced by our experimental conditions. At the breeding facilities, bitches are habituated to being temporarily separated from their litter (e.g., during daily walks) and accustomed to breeders manipulating puppies during daily care (e.g., weight measurements evaluating physical condition of puppies). It was thus unlikely that we induced stressful behaviours in mothers while recording their puppies. In addition, when bringing the puppy back to its mother, the observation of normal maternal behaviours such as grooming or breastfeeding [34] indicated low stress levels.
172

173 *Stimulus creation*

174 From this pool of acoustic recordings of natural puppy vocalisations, we used 10 whine

175 sequences at each age category (i.e., 1-, 3-, 6-, 9-week-old, 40 sequences in total) from 26

176 different individuals as templates to create their associated fully synthetic copy (hereafter
177 synthetic prototype). We choose whine sequences composed of three repeated whines

178 without NLP to facilitate their synthesis with the R package *soundgen* [31].

179 For each synthetic prototype, we prepared sets of vocalisations with systematic
180 manipulations of NLP and *f*<sub>o</sub> (Table 1) for playback experiments. Specifically, we created
181 synthetic whine stimuli at low, medium, and high levels of *f*<sub>o</sub>, with or without different types
182 of NLP added at each *f*<sub>o</sub> level, based on those that naturally occur in puppy whines, including
183 frequency jumps or varying proportions of subharmonics, sidebands, and chaos (Fig. 1).

184 Manipulations of NLP and *f*<sub>o</sub> were applied to the three repeated whines composing the
185 entire synthetic prototype.

186 To inform these manipulations, we first performed detailed acoustic analyses on our
187 recorded whines to characterise the natural vocal variation in puppy whines (see electronic
188 supplementary material). We manually measured onset time and proportion of NLP as well
189 as the *f*<sub>o</sub> of 4841 natural whines containing NLP. This allowed us to create highly realistic
190 variants that remained within the range of natural production, thus increasing the ecological
191 validity of our experimental method and reliability of our results.

192 In total, there were 300 stimuli in Experiments 1 and 3: 20 prototypes * 5 NLP conditions
193 (none, frequency jump, subharmonics, chaos, sidebands) * 3 *f*<sub>o</sub> levels (low, medium, high).

194 Experiment 2 included 840 stimuli: 40 prototypes * 7 conditions of NLP duration (none +
195 50% or 80% of the whine duration affected by subharmonics, sidebands, chaos = 1+ 2*3 = 7)
196 * 3 f<sub>o</sub> levels. All audio stimuli and R code for their synthesis are available for download at
197 https://osf.io/rp7m8/.

198

199 *1- Manipulations of nonlinear phenomena*

200 Experiments 1 and 3 tested perceptual effects of the presence or absence of NLP in puppy

201 whines. We manually coded frequency jumps as instantaneous changes in *f*<sub>o</sub> occurring at
202 the maximum *f*<sub>o</sub> slope. Indeed, as the production of NLP is typically associated with

203 increases in subglottal pressure, leading to a relatively high *f*<sub>o</sub> and amplitude, and ultimately,
to an unstable vocal system [3,39], NLP are expected to occur in sections of calls where $f_0$ is relatively high [40]. We also added sidebands, subharmonics, and chaos to whines by randomly selecting the onset time from the observed natural distribution. Durations of these types of NLP were selected at random within an interval corresponding to the most commonly produced NLP durations in natural whines, i.e., 20% to 40% of the whine's duration (Fig. S1).

Experiment 2 tested perceptual effects of NLP duration. Here, the duration of NLP was fixed at either 50% (hereafter medium proportion) or 80% (hereafter high proportion) of the variant's duration (Fig. 1.a), both of which remained within the natural range (Fig. S1). The onset time of NLP was also randomly selected from the observed natural distribution, but under the constraint that the onset time should be within a specific interval (medium proportion: [0; 50] % of the whine duration, high proportion: [0; 20] % of the duration).

We synthesized subharmonics, sidebands, and chaos using a method allowing for natural variability. Specifically, to synthesise subharmonics, the integer ratio of subharmonic frequencies to $f_0$ was drawn from a truncated Poisson observed distribution (mean=1 and range= [2, 5]), typically resulting in additional spectral components (subharmonics) at $f_0/2$ or $f_0/3$. We created sidebands by adding amplitude modulation, the frequency of which was selected from a Gaussian distribution (mean ± SD = 170 ± 20 Hz) characterizing sidebands in natural puppy whines. The amplitude of subharmonics and sidebands, expressed as the proportion of the amplitude of $f_0$, was randomly selected from a Gaussian distribution with a mean ± SD of 50% ± 10% [3] and 80% ± 10%, respectively. Finally, we created chaos by adding jitter (i.e., changes in $f_0$ periodicity) with values of 3 ± 0.6 semitones in Experiments 1 and 3, and 1.2 ± 0.3 semitones in Experiment 2, such that chaotic episodes sounded natural.

## 2- Manipulations of $f_0$

Because variations in $f_0$ can affect perceptions of distress [41–44], size [45,46], and dominance [47], we also tested whether perceptual effects of NLP vary across $f_0$ levels.

From our $f_0$ measurements of natural whines containing NLP, we identified three main $f_0$ categories that roughly correspond to quartiles of the natural distribution with a mean ± semitones/2 of 790 ± 27 Hz (low $f_0$), 972 ± 27 Hz (medium $f_0$), and 1170 ± 27 Hz (high $f_0$), hereafter termed target region. We thus synthesised stimuli at each $f_0$ level by first randomly selecting a target $f_0$ value from each target region. This allowed for natural
236 variability in $f_o$ across variants within each target region. Second, we calculated a coefficient
237 of correction as the ratio between the target $f_o$ value and average $f_o$ across whines in the
238 original synthetic prototype. Third, the $f_o$ of the prototype was corrected by this coefficient,
239 such that the average $f_o$ of the new variant reflected the target $f_o$ value.

<figure><img src="image_2.png" /></figure>

240

241 **Figure 1:** Spectrograms of variants of the same whine prototype synthesized with or without
242 NLP (frequency jumps, subharmonics, sidebands, chaos) at different levels of (a) NLP
243 duration (NLP affecting 50% or 80% of the whine's duration, as illustrated with the addition
244 of chaos) and (b) $f_o$ (low, medium, high). While every NLP manipulation was tested at every
245 $f_o$ level, here we show a range of NLP manipulations at each $f_o$ level as examples.

246

247 *Playback experiments with human listeners*

248 We performed online playback experiments on 487 human adult listeners (N= 206
249 Experiment 1; N= 221 Experiment 2; N= 55 Experiment 3). Before each experiment,
250 participants completed a short questionnaire indicating their sex, age, profession, level of
251 comfort with puppies and experience with puppy-ownership. They were also informed that
252 they would hear distressed puppy whines recorded during separation from mothers and
253 littermates. Because the term "puppy" can refer to both pre- and post-weaned dogs, we
254 defined a puppy as a dog younger than 3 months of age in our online questionnaire.
255 Participants first listen to three natural whine sequences containing NLP to familiarise
256 themselves with nonlinear puppy whines and to adjust their sound level to a comfortable
volume, which was then kept constant for the experiment. We asked participants to use
headphones when completing the experiment in a quiet environment.

Playback experiments comprised three blocks testing perceived distress, size, or dominance.

The order of blocks and stimuli within blocks were randomized. Each block contained 20
(Experiments 1 and 3) or 40 (Experiment 2) whine stimuli, such that each prototype was
tested once per block with a randomly chosen level of f₀ and NLP condition for a given
participant who listened to a total of 60 stimuli (Experiments 1 and 3) or 120 stimuli
(Experiment 2). Following each whine exposure, participants rated the whine by indicating
how distressed/dominant/large the puppy sounds, using a continuous sliding scale ranging
from 0 (Not at all distressed/dominant or extremely small) to 100 (Extremely
distressed/dominant/large). Participants could listen to stimuli several times and could
adjust their rating if needed.

In Experiments 1 and 2, we respectively excluded 6 and 4 participants who completed less
than 80% of the experiment or otherwise failed to engage with the study. No participant
from Experiment 3 was excluded. Statistical analyses were thus performed on 472
participants (N= 200 Experiment 1, N= 217 Experiment 2, N= 55 Experiment 3), aged 28 ± 11
years old (mean ± SD) (range [18-74]), of whom 40% self-reported as female, 60% as male,
and less than 1% as 'other'. Nearly all participants in Experiments 1 and 2 (409/417) did not
professionally work with puppies but felt comfortable in their presence (381/417), and 65%
had owned a puppy within the past 5 years. In Experiment 3, we specifically selected
participants for their extensive experience in puppy caregiving, and thus their regular
exposure to whines. Most of these participants professionally worked with puppies, as out
of 55, 40 were dog breeders, 12 were veterinarians, and 2 were dog trainers.

280

281 *Data analysis*

Data from playback experiments were analysed using Bayesian multilevel models fitted with the *brms* R package [48] using default priors. The response variable of models corresponded to ratings re-coded from 0 to 1 and modelled with zero-one-inflated beta distribution [49]. To investigate whether the presence of NLP affected human perceptions of puppy whines, and whether these effects of NLP varied with whine *f*₀, we first fitted a model including data from Experiments 1 and 2, testing the general population (N=417 participants). This model included a three-way interaction between the tested perceptual scales (3 levels), NLP
condition (5 levels) and $f_o$ (3 levels). We allowed effects of NLP on each scale to vary across
participants and prototypes by fitting the interaction between NLP and scale as random
slopes for all participants and prototypes. We also assumed that each stimulus would have
its unique rating on each scale. This model resulted in the following *brms* syntax:

Rating response ~ scale*NLP*f<sub>o</sub> + (NLP * scale|participant) + (NLP * scale|prototype) +
(scale|stimulus)

To examine whether experience in puppy caregiving influences the effects of NLP, we fit an
analogous model to the data collected from experienced caregivers (N=55 participants in
Experiment 3). Finally, we tested whether the duration of NLP reinforced their perceptual
effects by fitting a second model with data from Experiment 2 (N= 217 participants). This
model included a two-way interaction between rating scales and duration of NLP (7 levels).

The model followed this *brms* syntax:

Rating response ~ scale*duration + (scale*duration| participant) +
(scale*duration|prototype) + (scale|stimulus)

In this model, we captured an assumed variability of predictors *scale* and *duration* across
participants and prototypes and allowed for ratings of each scale to vary across each unique
stimulus. Posterior distributions of model parameters were summarized by their median and
95% credible interval.

307

## Results

We predicted that the presence and duration of NLP in puppy whines would increase
perceptions of distress, size, and dominance by human listeners. With the exception of
frequency jumps, all NLP affected listeners' ratings on one or more of these perceptual
scales (Fig. 2.a, Fig. 3, Fig. S2.a).

Specifically, in the general population (Experiments 1 and 2), we found that perceptions of
distress were primarily affected by chaos, which increased distress ratings by 5.6% [3.8, 7.4]
compared to identical whines without NLP. In contrast, distress ratings were not noticeably
affected by the addition of subharmonics (-0.7% [-2.1, 0.7]) nor sidebands (1.3% [0, 2.6]).

Experienced puppy caregivers (Experiment 3) also rated whines with chaos as more
distressed-sounding, but unlike the general population, they furthermore associated
319 sidebands and subharmonics with higher distress (see electronic supplementary material for details, Fig. S2.a).

320 Moreover, we predicted that longer episodes of subharmonics, sidebands, and chaos in 321 puppy whines would increase their perceptual salience and thus, enhance their effects on 322 perceived distress. Surprisingly, we found that increasing the duration of chaos from 50% to 323 80% of the whine's duration did not further increase perceived distress (-0.4% [-3.0, 2.3]), 324 and that increasing the duration of subharmonics and sidebands reduced perceived distress 325 by 4.8% [2.2, 7.5] and 3.1% [0.8, 5.4], respectively (Fig. 3).

326 While effects of NLP were relatively stable across each $f_0$ level, our results confirm an 327 independent effect of $f_0$ on distress ratings in participants for all three experiments (Fig. 2.b 328 and c; Fig. S2.b and c). Indeed, puppies producing whines with higher levels of $f_0$ were rated 329 as more distressed (9.3% [8.1, 10.6]), compared to the same whines synthesized at lower $f_0$ 330 levels (Fig. 2b).

331 In addition to effects on perceived distress, our results show that the general population 332 (Experiments 1 and 2) rated size and dominance about 4% to 6% higher in whines containing 333 subharmonics, sidebands, or chaos, compared to whines without NLP (Fig. 2.a). However, 334 these effects were absent or limited in experienced puppy caregivers (Fig. S2.a).

335 We also predicted that increasing the duration of subharmonics, sidebands, or chaos from 336 50% to 80% of the whines' durations would reinforce their effects on perceived size and 337 dominance. Our results indeed show that whines containing 80% of subharmonics (but not 338 chaos and sidebands) increased perceived size by 6% [3.0, 8.9] and perceived dominance by 339 5.1% [2.3, 7.7] compared to the same whines with only 50% of these NLP (Fig. 3).

340 Finally, we found no interactions between NLP and $f_0$ levels in the general population 341 (Fig.2c), instead confirming an independent effect of $f_0$ on perceived size and dominance 342 (Fig.2b): whines with a lower $f_0$ were systematically associated with larger (12.9% [14.1, 343 11.7]) and more dominant (5.9% [-7, -4.8]) sounding puppies, relative to the same whines 344 synthesized at higher levels of $f_0$. Similar results were found for experienced puppy 345 caregivers (Fig. S2.b and c).

346

347
<figure><img src="image_3.png" /><figcaption>**Figure 2:** Main effects of (a) NLP, (b) *f*<sub>o</sub>, and (c) interactions between NLP and *f*<sub>o</sub> on perceived distress, size, and dominance (N=417, Experiments 1 and 2). Solid markers correspond to medians of posterior distribution with their 95% credible intervals.</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>**Figure 3:** Effects of NLP duration on perceived distress, size, and dominance in Experiment 2 (N=217). A duration of zero corresponds to whines without NLP. Solid markers correspond to medians of posterior distribution with their 95% credible intervals.</figcaption></figure>
We investigated the independent perceptual effects of nonlinear phenomena (NLP) that occur naturally in a non-human animal vocalisation, namely in distressed puppy whines. By applying an innovative method of parametric sound synthesis in the context of interspecific vocal communication, we show that the presence and duration of different NLP types in puppy whines generally increase their perceived distress, size, or dominance, as judged by human listeners.

We found that the presence of chaos in puppy whines, but not the addition of frequency jumps, sidebands, or subharmonics, increased perceptions of distress in human listeners representing the general population. From a biomechanical perspective, the production of NLP, particularly chaos, is typically associated with high subglottal pressure and strong muscle tension on vocal folds [39] - configurations of the vocal apparatus that are likely to arise in distressed animals with highly aroused physiological states [1]. Chaos is indeed a characteristic of calls associated with distress in a wide range of mammals ([10,15,16,21,23], this study). Additionally, at the perceptual level, Blumstein and Récapet (2009) [24] have shown that white noise (which shares some perceptual elements with deterministic chaos [50]) added to natural alarm calls of marmots induces potentially costly responses in these animals (reduced foraging activity). An earlier study also showed that chaos added to human nonverbal vocalisations increases the intensity of perceived negative, rather than positive, affective states [51]. Together, our findings thus support that chaos is perceived as a vocal indicator of higher levels of distress in mammals.

As increases in subglottal pressure, characterised by high amplitude and $f_0$, often lead to vocal instability [3,39], NLP are expected to occur when $f_0$ is relatively high. For instance, the onset of NLP corresponds with the maximum $f_0$ in chimpanzees' calls [40]. As such, it is difficult to disentangle the effect of $f_0$ from the effect of NLP when performing playback experiments using natural calls [9,24,25], as these acoustic parameters may covary. To overcome this limitation, we used synthetic stimuli varying in the presence and duration of NLP at different $f_0$ levels. While we confirmed that perceived distress increases
independently with $f_o$, as reported in numerous previous studies [41–44], the effect of NLP on the perception of distress was relatively stable across all $f_o$ levels. This suggests that perceptual effects of $f_o$ and NLP are independent and cumulative, and that both are salient vocal indicators of distress.

Contrary to our prediction, whines containing relatively longer episodes of chaos did not increase perceived distress compared to whines with less chaos, suggesting that a ceiling effect may have been attained with chaos affecting only half of the call duration. Indeed, listeners may have applied a categorical decision (no chaos = relatively low distress, chaos = relatively high distress) when exposed to whines with or without chaos. Moreover, for sidebands and subharmonics (whose presence did not affect perceived distress in the general population), we found that perceived distress was lower in variants containing longer episodes of these NLP. We suggest that bifurcations between the tonal and non-tonal sections of the calls may be less salient in calls with a largely dominant non-linear regime. In a recent study, we showed that subharmonics and sidebands added to human nonverbal vocalisations lowered their perceived pitch [18]. As such, when exposed to subharmonics or sidebands affecting 80% of the whine duration, listeners may have perceived these calls with a relatively high tonality at a lower $f_o$ and may thus have associated these lower-pitched sounds with behavioural contexts of aggression, rather than distress. This would follow Morton's motivation-structural rules stating that aggressive animals typically produce low-pitched sounds, whereas distressed, fearful animals produce high-pitched sounds [28].

### *Nonlinearities increase perceptions of size and dominance*

Experimentally adding subharmonics, sidebands, and chaos - but not frequency jumps - to whines increased the puppy's perceived body size and dominance. Increasing the duration of subharmonics further increased perceived size and dominance. These results are consistent with recent work on human nonverbal vocalisations [18,32]. Our results also confirm the well-established perceptual effect of $f_o$ on size and dominance [45–47] – whines with a relatively low $f_o$ were systematically perceived as produced by larger and more dominant-sounding puppies, independent of the effects of NLP on perceived size and dominance. Although we show that $f_o$ directly affects perceptions of size and dominance, we cannot completely rule out the possibility that NLP independently lower the perceived pitch of whines (as they do in human vocalisations) [18]. This pitch-lowering effect may thus
420 be one of the perceptual mechanisms whereby NLP cause puppies to sound larger and more
421 dominant. This prediction could be directly tested in future work by simultaneously
422 assessing the effect of NLP manipulations on auditory (pitch, timbre) and ecological
423 (distress, dominance, etc.) dimensions.

424 The pitch-lowering effect of NLP has been hypothesised as a possible strategy for animals to
425 exaggerate perceived size and dominance [4,5]. Indeed, frequency components such as
426 formant frequencies and/or f₀ mediate the vocal communication of size and dominance,
427 which are crucial factors affecting the outcome of social interactions, such as mating, sexual
428 competition, or territorial defence [2]. Many species have developed strategies to
429 exaggerate their apparent size and, potentially, also their dominance (reviewed in [27] and
430 [52]), with specific adaptations to their vocal apparatuses such as a descended and mobile
431 larynx [53]. Because there is no clear biological function for a puppy to sound larger and
432 more dominant to humans while producing a distress vocalisation, we suggest here that the
433 perceptual effects of NLP on size and dominance are likely the consequence of a general
434 perceptual bias linking "harsh" with "large and dominant" [18].

435

436 *Effect of experience on listener perception of puppy whines*

437 While infant distress calls conveying need to parents are ubiquitous in vertebrates [22], in
438 the context of domestication, these distress calls may also function to communicate need to
439 heterospecific caregivers. Indeed, human baby pain cries are often characterised by very
440 high levels of NLP [16] and human listeners pay attention to these acoustic features to
441 assess a baby's level of distress and need [16]. As such, the production of whines, and within
442 them the production of NLP, may have been encouraged by dog domestication, with
443 puppies exploiting human sensitivity to chaos in offspring calls. Breeders indeed do
444 intervene and provide care to puppies [35], e.g. in the case of mother neglect, aggression, or
445 rejection [34]. Consistent with this, when asked to characterise how they react when
446 exposed to puppy whines in their normal professional activities, more than 50% of our
447 experienced puppy caregivers reported being negatively affected by whines, paying
448 attention to their harshness and roughness, and using these acoustic features as cues to
449 distress in order to adjust the level of care they provide to the puppies. Interestingly, while
450 experienced caregivers were as sensitive to chaos as the general population when rating
451 perceived distress, they also associated subharmonics and sidebands with higher levels of
distress (unlike the general population), as also observed in other species (e.g., subharmonics in meerkats: [9]). Together these results suggest that human sensitivity to chaos, the most severe form of NLP, has a universal base when assessing distress in puppy whines, but that sensitivity to other NLP can also arise with extensive experience. To further investigate the possibility that domestication may have emphasised whining and NLP within puppy whines as a consequence of sensory exploitation of caregivers (or as a consequence of relaxed predation pressures [54]), future studies should contrast the production of NLP within the whines of domestic dog puppies and wolf pups (*Canis lupus*).

Finally, NLP had little effect on perceptions of size and dominance in experienced caregivers, suggesting that their extensive experience allows them to correct for the perceptual bias identified in our general population. At the same time, experienced caregivers remained sensitive to whine $f_0$ when assessing distress, size and dominance. This suggests that $f_0$ may function as a reliable index of these traits in puppy vocalisations, as identified for distress and size in adult dog whines [55,56]) and in the calls of other mammals [1,2], a hypothesis that we are currently investigating.

## Perspectives

It remains to be established whether NLP signal distress information in puppy-mother vocal interactions, as they do to human listeners. Indeed, a recent study reports a positive relationship between the level of jitter (“noisiness”) in natural distress puppy whines and the strength of adult dogs’ behavioural responses [57]. Furthermore, although whines are typically associated with distress contexts, the domestic dog’s vocal repertoire also includes vocalisation types that are produced in both positive (e.g., playful) and negative (e.g., agonistic) contexts, such as growls or barks [58,59]. In addition to signalling relatively stable physical attributes (e.g., size) [60], these vocalisations can vary acoustically between positive and negative behavioural contexts [56,61]. For example, high-pitched and tonal barks are produced in playful contexts whereas low-pitched and harsh, chaotic barks are more commonly produced during territorial defence [56]. Nonlinear phenomena in barks or growls may thus function to communicate aggressive intent (rather than play) and, in such an agonistic context, may also function to exaggerate size and dominance. This prediction may be tested in the contexts of both inter- and intra-specific vocal communication. We thus suggest that using methods of parametric sound synthesis, as reported here, could be
484 generalised to a wider range of species and contexts to directly test the communicative function of NLP in animal vocal communication.

486

487 **Ethics**

488 Acoustic recordings of puppies were performed under the ethical Approval no. E-42-218-0901 (ENES lab agreement, Direction Départementale de la Protection des Populations, Préfecture du Rhône). All human participants provided informed consent, and ethical approval for performing perceptual experiments with human subjects was provided by the Comité d'Ethique du CHU de Saint-Etienne (IRBN692019/CHUSTE).

493

494 **Data accessibility**

495 All audio stimuli, R codes for synthetizing stimuli, html code for running psychoacoustic experiments, datasets as well as R codes for analysing data can be downloaded from https://osf.io/rp7m8/.

498

499 **Author's contributions**

500 All authors designed the study. M.M. collected the data; M.M. and A.A. created the stimuli and performed the data analyses; M.M. wrote the original draft. All authors reviewed and edited the manuscript and gave their final approval for publication; D.R. Supervised the study.

504

505 **Competing interests**

506 The authors declare no competing interests.

507

508 **Funding**

509 M.M. and D.R. were supported by the University of Lyon IDEXLYON project as part of the 'Programme Investissements d'Avenir' (ANR-16-IDEX-0005) to D.R. A.A. was supported by grant 2020-06352 from the Swedish Research Council. D.R & N.M. were supported by the Institut Universitaire de France. Funding was provided by LabEx CeLyA, CNRS, INSERM, University of St-Etienne.

514

515 **Acknowledgments**
516 We thank Professor Alain Fontbonne for kindly putting us in contact with his network of dog

517 breeders. We also thank the dog breeders who allowed us to record puppies at their

518 facilities.

519

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