Subjects

Out of the 71 pet dogs that took part into the experiment, a small proportion of subjects (n = 8) failed to react to the audio stimuli (see below for detailed information about stimuli) and were excluded from our analyses. So, participants were 63 pet dogs of various breeds, involved in the study on the basis of their owners’ volunteer participation. Forty-four adult dogs (average age of 3.74 years, range: 1 year to 14.25 years) and 19 puppies (less than one year, average age of 3.53 months, range: 2 months to 6 months) were tested (see supplementary material, Table S1 for details).

Experimental stimuli

Nine women (age M = 31.37, SD = 10.53, see supplementary material, Table S2 for details) naive to the purpose of this study were recorded to provide audio clips of 3 different types of speech: ADS, IDS and PDS. The recordings were performed in a silent room of the laboratory Ethology Cognition and Development at the University of Nanterre. Women speaker were equipped with a lapel microphone (Olympus ME-15) connected to a MARANTZ PMD620 digital recorder. Samples were collected in ‘wav’ format with sampling frequency of 44100 Hz.

In a recent study, Ben-Aderet et al.28 obtained dog-directed speech by asking women to speak in front of dogs’ pictures. In order to provide more ecological validity to our data, our recordings were performed during interaction with real dogs, infants and adult. Thus, in a pseudo-randomized design, women were asked to address a single sentence: “On va se promener?” (“Shall we go for a stroll?”) (1) to a dog (a 2 years old Labrador Retriever, a 18 months old Chihuahua or a 18 months Maltese), (2) to an infant (either a 4 months old girl or a 3 months old girl), and (3) to the researcher (always the same) performing the recordings. The sentence was agreed in advance; we chose this sentence because it can be addressed similarly to an adult, to an infant or to a dog. There was one trial per condition (ADS, IDS, PDS). Women speaker were instructed to attract the interlocutor’s attention by saying his/her name before speaking.

Acoustic analyses were performed using PRAAT to ensure that IDS and PDS were distinct from ADS (see Results section). Twenty seven audio clips were created using Audacity® software corresponding to the 3 type of speech (ADS, IDS, PDS) for each of the 9 women. Each audio clip was composed by the 3 sentences, each lasting between 0.52 to 1.52 seconds depending to the speed of delivery (X ± SD = 0.69 ± 0.18 seconds), spoken by the same woman and separated by 2 seconds’ silence, a 0.6 second pink noise and another 2 seconds’ silence, as presented in Fig. 2. The diffusion of a pink noise between two sentences intended to attract dog’s attention and dampen the process of habituation. The order of the speeches within a clip was randomized. Each audio clip lasted between 16.72 and 17.77 seconds (X ± SD = 17.29 ± 0.06 seconds). Men voices were not recorded in order to match the gender of the voices diffused and the gender of the experimenter placed in front of the dog, as there is evidence that dogs can match male faces to voices46, 47.

Figure 2 Example of an audio clip. Open squares correspond to human speeches: Adult-Directed Speech (ADS), Infant-Directed Speech (IDS) or Pet-Directed Speech (PDS) (duration: 0.69 ± 0.18 s). Grey squares correspond to pink noise (0.6 s) and lines correspond to silences (2 s). Full size image

Procedure

The experiment was carried out at the Ecole Nationale Vétérinaire d’Alfort, France (ENVA). The protocols were approved by the Ethics Committee for Clinical Research (Comité d’Ethique en Recherche Clinique, ComERC) of ENVA, n° 2015-03-11. All methods were performed in accordance with the relevant guidelines and regulations. Informed consent was obtained from all participants. Participants were debriefed about the aims of the study at the end of the experiment. Seventy-one owner and dog dyads were recruited in the waiting room of the preventive medicine consultation of the Centre Hospitalier Universitaire Vétérinaire d’Alfort (CHUVA) and through veterinary students’ social networks. Participants whose dogs presented significant health problem, aggressiveness toward people, sight or hearing problems were not tested. The aim of the research was presented to the participants as follows: ‘we would like to explore what dogs perceive from human language’.

Apparatus

The study was performed in a 24 m² room. Videos were recorded using a Canon (Legria HF R306) recorder mounted on a tripod positioned at the back-center of the room in front of a loudspeaker (Anchor MiniVox Lite) connected to a computer disposed on a table of 1 m high. The chair where the owner was sitting was aligned with the video recorder and the loudspeaker. A sonometer (Ro-Line SPL meter, R0-1350) was used to measure the sound intensity: all sounds were 90 decibels.

Experimental protocol

Initially, the owner was asked about his/her dog’s name, age and breed, composition of the family etc., while the dog was let free to explore the room. Then he/she was invited to sit on a chair placed in front of the video recorder and to install his/her dog between his/her legs or to put him on his/her knees. Because prior studies found that dogs often ignore vocal commands given by humans (or recordings of humans) if no human is physically present48, 49, a female experimenter (S.J.) was constantly present, standing in front of the loudspeaker in order to increase the likelihood that the dog would pay attention to the vocal recordings played by the loudspeaker (Fig. 3). The experimenter adjusted the video image for each dog so that the dog was in the central part of the image. Blinded to the playback order, the experiment launched the audio sequence, using the computer behind her, when the dog was calm and well positioned, using the computer behind her. Few seconds of silence were programmed before the playback starts to allow time for the experimenter to position and remain immobile. The experimenter looked straight in front of her to avoid eye contact with the dog. Owners were asked not to speak or stroke the dog during the playback. Each dog listened to one randomly selected audio sequence.

Figure 3 Schematic drawing of the setup. Full size image

Data analyses

Acoustic analyses

In order to verify that the recordings used for the playbacks had characteristics properties of ADS, IDS or PDS, acoustic analyses were performed using a script Praat software (5.3.50)50. We treated each recording as one continuous vocalization; the analysis was made on utterance level. We measured the following parameters: (a) duration: the total duration of the recording; (b) Mean F0: the average fundamental frequency F0 calculated over the duration of the signal; (c) Diff ES: the difference between mean F0 at the end of the recording and mean F0 at the start of the recording. Diff ES is considered to be an indicator of the intonation contour; (d) Range F0: the range of the fundamental frequency F0; (e) F0CV: the coefficient of variation of F0 over the duration of the signal, estimated as the standard deviation of F0 divided by mean F0; (f) IntCV: the coefficient of variation of the intensity contour.

Additional acoustic analyses

Further analyses were made on supplementary parameters (harmonicity, shimmer, jitter, the first three formant frequencies of the vocal stimuli). Moreover, because previous studies showed a significant difference between IDS, PDS and ADS based on vowel hyperarticulation3, we measured this parameter using Andruski et al.’ procedure51; vowel hyperarticulation was objectified by plotting first and second formant (F1 and F2) values of the determinant vowels of the sentence “on va se promener?”: a [a], o [o], and é [e], and comparing the resultant vowel triangles (see supplementary results, Figure S1 for details). The acoustic space encompassed by the 3 point vowel categories was compared by calculating the area of the vowel triangle for each type of speech. Vowel triangle area was calculated as: 1/2*[X1(Y2-Y3) + X2(Y3-Y1) + X3 (Y1-Y2)] where X and Y are the mean F1 and F2 values, and 1, 2, and 3 are the point vowels, [a], [o], and [e].

Video coding

Dogs’ behavioural response to human vocal stimuli was recorded and analyzed with Solomon Coder software (version beta 16.06.26). We made continuous observations from videos with a time-precise of one-tenth of a second. For each dog and for each vocal stimulus (ADS, IDS, and PDS), we measured the total duration of looks toward the loudspeaker, referred as “gaze duration” in our statistical analysis. This measure is the standard one used to assess infants’ attention18, 19. Moreover, it was used in previous studies to assess dogs’ attention and effect of various conditions on this parameter (i.e. aging29; relationship30; oxytocin22). In order to take the variability of stimulus duration (from 0.52 to 1.52 seconds) gaze duration toward the loudspeaker, was expressed as the relation between the gaze duration and the stimulus duration.

Statistical analyses

Acoustic analyses

The normality of the data was tested using Shapiro-Wilk tests. To test whether the recording order and the type of speech influenced the acoustic features of women speakers, we used general linear mixed models (GLMMs) using library ‘lme4’ of the R software. For each acoustic feature, we constructed model with the type of speech, the recording order and their interaction as fixed effects and the identity of the speaker as random effects. We first tested the model with the interaction against the model without the interaction. If the interaction was no significant, we removed it from the model and then tested one-factor models (either type of speech or recording order) against the minimal model. Finally, we performed Tukey post hoc tests when appropriated, using library ‘multcomp’ of the R software; Tukey test was developed specifically to account for multiple comparison and maintains experiment-wise alpha at the specified level (0.05)52. Statistics were performed using R© version 3.2.4 (The R foundation for statistical computing, Vienna, Austria).

Analysis of dogs’ behavioural response to playback

To test for differences in type of speech on dogs’ behaviour, we used GLMM with the glmer function of the package ‘lme4’ using R© version 3.2.4. GLMMs allowed us to build a model with both fixed effects and random effects, and to specify data distribution (here a binomial distribution). To take into account the variation of the duration of the stimuli, ‘Gaze duration’ divided by ‘Stimulus duration’ was set as the dependent variable; ‘Stimulus duration’ was thus specified as a ‘weights’ argument in the model. The dog’s identity was specified as the random factor to control for repeated measures. Dog familiarity with people of both gender referred as “dog familiarity to gender” (women only, men only, both sexes), the presence of children at home (yes or no), dog age (adult vs. puppy), dog sex (male vs. female), type of speech (ADS, IDS, PDS), playback order (first, second or third position) and their interaction were specified as the fixed factors. Likelihood-ratio tests were performed to obtain P values by comparing the full models with reduced models (without the fixed effect). If appropriate, these analyses were followed by Tukey post hoc tests using the glht function of the package ‘multcomp’.

Moreover, to assess how the different acoustic features affected dogs’ attention, we built a model for each acoustic feature that significantly differentiated ADS from IDS and PDS. Hence, the acoustic feature, dog age, their interactions and playback order were specified as fixed factors. As in previous analyses, ‘Gaze duration’ divided by ‘Stimulus duration’ was set as the dependent variable (‘Stimulus duration’ was specified as a ‘weights’ argument in the model). The dog’s identity was specified as the random factor to control for repeated measures. P values were obtained with likelihood-ratio tests comparing the models with interaction and models without interaction.

Significant interactions were followed by Pearson correlations in order to assess the relationship between acoustic features and dogs’ attention for each age (adult dogs and puppies) and for each type of speech (ADS, IDS and PDS).

Ethical approval

The study received the approval of the ethical committee of ENVA (COMERC), 477 n° 2015-03-11.