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. 2017 May 8;141(5):3145–3150. doi: 10.1121/1.4982727

The development of gaze to a speaking face

Julia Irwin 1,a), Lawrence Brancazio 2,b), Nicole Volpe 2
PMCID: PMC5422207  PMID: 28599552

Abstract

When a speaker talks, the visible consequences of what they are saying can be seen. Listeners are influenced by this visible speech both in a noisy listening environment and even when auditory speech can easily be heard. While visible influence on heard speech has been reported to increase from early to late childhood, little is known about the mechanism that underlies this developmental trend. One possible account of developmental differences is that looking behavior to the face of a speaker changes with age. To examine this possibility, the gaze to a speaking face was examined in children from 5 to 10 yrs of age and adults. Participants viewed a speaker's face in a range of conditions that elicit looking: in a visual only (speech reading) condition, in the presence of auditory noise (speech in noise) condition, and in an audiovisual mismatch (McGurk) condition. Results indicate an increase in gaze on the face, and specifically, to the mouth of a speaker between the ages of 5 and 10 for all conditions. This change in looking behavior may help account for previous findings in the literature showing that visual influence on heard speech increases with development.

I. INTRODUCTION

Visual information about speech influences what listeners hear (Desjardins et al., 1997; Lachs and Pisoni, 2004; McGurk and MacDonald, 1976; MacDonald and McGurk, 1978; MacDonald et al., 2000; Reisberg et al., 1987). This visible articulatory information on a speaker's face is thought to be a central part of typical perceptual development and to foster native language acquisition (Legerstee, 1990) and has been demonstrated in infancy (Burnham and Dodd, 1998; Meltzoff and Kuhl, 1994; Rosenblum et al., 1997). Both understanding and producing speech is likely influenced by experience with seeing other talkers. For example, blind individuals display differences in speech perception and production in comparison to sighted individuals (Ménard et al., 2009). Further, visible speech can influence what is heard both in the context of a noisy background (e.g., Sumby and Pollack, 1954) and even in clear listening conditions. One powerful example of visual influence on what is heard in clear listening conditions is mismatched audiovisual (AV) speech. McGurk and MacDonald (1976) first discovered this by presenting mismatching audio and video consonant-vowel tokens to perceivers. Perceivers watching these dubbed productions sometimes reported hearing consonants that combined the places of articulation of the visual and auditory tokens (e.g., a visual /ba/ + auditory /ga/ heard as /bga/), “fused” the two places (e.g., a visual /ga/ + auditory /ba/ heard as /da/), or reflected the visual place information alone (a visual /va/ + auditory /ba/ heard as /va/).

In their classic paper described above, McGurk and MacDonald (1976) also reported that preschoolers (3–4 yr olds) and school-aged children (7–8 yr olds) are less influenced by visual speech information than are adults (also see Sekiyama and Burnham, 2008). Since then, a number of studies revealed that both visual influence in the context of a McGurk task and speechreading ability (identification of a syllable from visual information only) increases with age (Desjardins et al., 1997; Hockley and Polka, 1994; LaLonde and Frush Holt, 2014; Massaro, 1984; Massaro et al., 1986; Ross et al., 2011; Tremblay et al., 2007). According to this prior work, increased visual influence with development could be due to experience with producing speech sounds (motor experience: Desjardins et al., 1997 report visual influence for children if they can produce the sound that they see on another speaker's face), ongoing perceptual learning/tuning with respect to visual speech during childhood (ability to pick up phonetic information from the visual signal: Ross et al., 2011; Hockley and Polka, 1994), or that younger children were less attentive to the visual source, leading to an attenuated visual effect (changes in attention to the speaking face: Massaro, 1984).

Clearly, access to visual speech is necessary for AV speech perception. Adult listeners have been demonstrated to exhibit reduced visual influence on what is heard when asked to engage in a task that requires attention to another visual stimulus (e.g., attention to a shape on the face of the speaker; Alsius et al., 2005). Previous research using eye tracking to examine gaze to a speaking face in adults indicates a pattern of reduced gaze on the eyes and increased gaze on the nose and mouth in the context of auditory noise (Buchan et al., 2008; Vatikiotis-Bateson et al., 1998; Yi et al., 2013). In clear auditory listening conditions, Lansing and McConkie (2003) found that before and after a sentence is spoken perceivers gaze to the eyes of a speaker, while gaze is largely toward the mouth of the speaker during the production of the sentence. Barenholtz et al. (2016) report that gaze to the speaker's mouth is greater during speech tasks for an unfamiliar language in monolinguals, but not in bilinguals. Looking behavior to the face of a speaker is likely also a factor in how much children are influenced by visible speech. In particular, if the developmental trends are due to attention to the face of the speaker, this could be reflected in gaze (as indicated by the work in adults of Vatkiotis-Bateson et al., 1998 and Buchan et al., 2008) or a more central attentional difference (e.g., Alsius et al., 2005). A few studies have examined gaze to the face in infants and children. Lewkowicz and Hansen-Tift (2012) showed a shift in focus toward the mouth from the eyes of a speaker corresponding to the onset of producing speech in infants, suggesting that gaze to the mouth increases as children begin to speak. Typically developing children have been compared to those with autism spectrum disorders (ASDs; a social-communication disability whose hallmark is atypical gaze to other's faces and is frequently accompanied by delays in spoken language; Irwin and Brancazio, 2014; Johnels et al., 2014). These studies indicate that typically developing children look more on the mouth of the speaker than children with an ASD. Yet to be examined is how a pattern of gaze to a speaking face in typically developing school-aged children changes with development (which in turn might account for the developmental differences in visual influence reported in previous research). Thus, using a cross-sectional design and visual tracking methodology we sought to provide more data on pattern of gaze to the speaking face in development during a set of auditory, visual, and AV tasks in children from 5 to 10 yrs of age and in adult participants.

II. METHOD

A. Participants

Seventy-four participants completed this study: 54 children, sixteen 5–6 yr olds (10 girls and 6 boys, mean age 6 yrs old), twenty 7–8 yr olds (6 girls and 14 boys, mean age 7 yrs, 11 months), eighteen 9–10 yr olds (9 girls and 9 boys, mean age 10 yrs old), and 20 adults (10 women and 10 men, mean age 22 yrs, 1 month) recruited from the community in the greater New Haven, CT area. The participants were reported by their parents or (in the case of the adults) by self-report to have normal or corrected-to-normal hearing and vision. In addition, all participants were reported by their parents or by self-report to have no history of vision, hearing, speech, language, or learning problems.

III. MATERIALS

A. Speech stimuli

The speech stimuli were created from a recording of the productions of an adult male, monolingual, native speaker of American English. This speaker was audio- and video-recorded in a sound-attenuated recording booth producing a randomized list of the consonant-vowel (CV) syllables /ma/, /na/, /ga/. The speaker produced each CV with as similar duration and intonation as possible.

1. Visual only (speechreading) stimuli

The visual only stimuli were silent versions of the speaker producing /ma/ and /na/. In this condition, participants were told that they would see a man saying some sounds that they would not be able to hear, and then asked to report what they thought the man was saying, for a total of 20 trials.

2. Speech in noise stimuli

Noise was added to the 60 dB /ma/ and /na/ tokens to create a range of signal-to-noise ratio levels at 5, 0, −5, −10, −15, and −20 dB, from less to more noisy. The AV stimuli were the same auditory tokens with video of the speaker producing the same CV syllables. For both auditory and AV stimuli, there were 24 trials.

3. AV match and mismatch (McGurk) stimuli

The mismatch stimuli were dubbed by placing the audio track such that the point of consonant release at the beginning of the vowel for a new auditory token matched the point of release for the original token, at the resolution of a single video frame, for a total of 12 trials. Mismatched stimuli were always a visual /ga/ token paired with an auditory /ma/. Matched stimuli replaced the audio from tokens of the same CV (e.g., a /ma/ visual token paired with a different auditory /ma/), for a total of 16 trials.

For the speech in noise and the AV match–mismatch conditions, participants were instructed to watch and listen to the video display. They were then told that they would hear a man saying some sounds that were not words and to say out loud what they heard.

B. Visual tracking methodology

Visual tracking was assessed with an ASL model 504 pan/tilt remote tracking system (Applied Science Laboratories, Bedford MA), a remote video-based single eye tracker that uses bright pupil, coaxial illumination to track both pupil and corneal reflections at 120 Hz. To optimize the accuracy of the pupil coordinates obtained by the optical camera, this model has a magnetic head tracking unit that tracks the position of a small magnetic sensor attached to the head of the participant.

1. Procedure

After parental consent and child assent (children) or individual consent (adults) was obtained in accordance with the Yale University Institutional Review Board, all participants completed the experimental tasks in the eye-tracker. The participant was placed 60 in. in front of the monitor and eye-tracker, after which calibration of the participant's fixation points in the eye-tracker was completed. Prior to any stimulus presentation for each task, directions appeared on the monitor. These directions were read aloud to the participant by a researcher to ensure that the participant understood the task. In addition, two practice items for each condition were completed with the researcher present to confirm that the participant understood and could complete the task.

After every five trials, participants were presented with a slide of animated shapes and faces to maintain attention to the task. Tasks were blocked, with stimuli presented in random order within block. The inter-stimulus interval for all trials within the blocks was 3 s. The blocks were presented in a semi-random order. The auditory-only stimuli had to be presented first to be sure that the participants could discriminate the difference between /ma/ and /na/. Other than the first, auditory-only block, the rest of the blocks were presented in random order. All audio stimuli were presented at a comfortable listening level (60 dB) from a centrally located speaker under the eye-tracker, and visual stimuli were presented at a 640 × 480 aspect ratio on a centrally located video monitor.

IV. RESULTS

A. Patterns of gaze

Gaze was analyzed for each of the four age groups at five time bins that corresponded to significant events in the speech signal. The first bin (0–300 ms) is initial neutral rest position, the second bin (300–600 ms) is opening prior to consonant closing gesture, the third bin (600–900 ms) is closure for the /m/ or /n/, the fourth bin (900–1200 ms) includes the peak mouth opening for the vowel, and the last bin (1200–1500 ms) is return to rest at the end of the vowel (see Fig. 1).

FIG. 1.

FIG. 1.

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Image of video frames corresponding to time bins for /ma/.

There were two measures which were analyzed separately for the speechreading, speech in noise, and AV (McGurk) conditions: face, which was the percentage of time fixating on the face out of time gazing on the screen, and mouth, which was the percentage of time fixating on the mouth out of time gazing on the face (see Figs. 2, 3, and 4). For percentage of time on the face, all participants increased gaze to the face of the speaker once speech movement begins (see onset at 300 ms) until a plateau or slight decrease at 1200–1500 ms, where the speech signal is concluding. Critically, there was a significant main effect of age in all three tasks [speechreading: F (3, 70) = 5.68, p < 0.01; speech in noise: F (3, 70) = 7.25, p < 0.001; AV: F (3, 70) = 9.55, p < 0.0001]. In the three tasks, there was a developmental trend such that the younger children (5–6 and 7–8 yr olds) spent proportionally less time fixating on the face than older children (9–10 yr olds and adults). The difference between adults and 9–10 yr olds (higher mean fixations on the face for adults) was reliable only in the AV condition (p < 0.01). There were also significant age × time interactions in all three tasks, F (12, 280) = 4.36, p < 0.0001 for speech in noise; F (12, 280) = 5.59, p < 0.0001 for speechreading; F (12, 280) = 2.75, p < 0.001 for AV (McGurk) conditions, reflecting changes in the overall magnitude of the group differences as the stimulus was presented, but this did not alter the basic pattern of age-related differences.

FIG. 2.

FIG. 2.

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Percent of time on face: speechreading condition.

FIG. 3.

FIG. 3.

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Percent of time on face: speech in noise condition.

FIG. 4.

FIG. 4.

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Percent of time on face: AV (McGurk) condition.

For percentage of time on the mouth (Figs. 5, 6, and 7), there was again a significant main effect of age for speech reading F (3, 70) = 2.70, p < 0.05 and speech in noise, F (3, 70) = 5.61, p < 0.001, but not for AV, F (3, 70) = 1.3, ns. All three tasks had significant interactions of age × time (speech reading: F (12, 280) = 4.19, p < 0.0001; speech in noise: F (12, 280) = 5.43, p < 0.0001; AV: F (12, 280) = 2.75, p < 0.001). In all three tasks, the younger children (5–6 yr olds) spent less time fixating on the mouth region than the older children (ages 7–8 and 9–10 yrs old), who did not reliably differ. The interaction reflected the finding that the age difference emerged only when speech movement began (300 ms and onward); the older children exhibited a sharper increase in mouth fixations from the first bin to the third, with a more gradual increase for the younger children. Unlike in fixations on the face, adults did not exhibit a higher proportion of fixations on the mouth than the children; adults exhibited a relatively flat pattern of mouth fixations across the time bins; thus, by mid-stimulus (600–900 ms) they tended to have more mouth fixations than the youngest children (5–6 yrs old) but fewer than the older children (7–8 and 9–10 yrs old).

FIG. 5.

FIG. 5.

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Percent of time on mouth out of time on face: speechreading.

FIG. 6.

FIG. 6.

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Percent of time on mouth out of time on face: speech in noise condition.

FIG. 7.

FIG. 7.

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Percent of time on mouth out of time on face: AV (McGurk) condition.

We also examined gaze to the eyes, nose, and to non-focal areas of the face (areas other than the eyes, nose, and mouth). There were no significant effects between groups for these areas.1

V. DISCUSSION

Developmental trends in visual influence on heard speech have been reported in the literature, with a range of possible explanations for this effect, including motor experience, ability to pick up phonetic information from the visual signal and attention. The current study investigated whether there are developmental changes in gaze to relevant areas of the speaking face, a necessary precursor to determining whether such changes could underlie changes in visual influence.

Our data showed an increase in gaze on the face, specifically in fixations on the mouth of a speaker, between the ages of 5 and 10 for speech reading, AV speech in auditory noise, and mismatched AV (McGurk) speech. These results reveal a potential explanatory factor for previously reported findings of increased visual influence with development: an increase in fixation (and possibly visual attention) to the mouth of the speaker. The current data suggest that while adults show a high percentage of time on face relative to children, they do not show a great deal of time fixating on the mouth. Interestingly, previous research by Vatikiotis-Bateson et al. (1998) and Paré et al. (2003) demonstrates that direct gaze on the mouth of the speaker is not required for influence of visual articulatory information in typically developing adults, however, this may not be the case for younger listeners. In particular, the youngest listeners (5–6 yr olds) appear to be less focused on the speaker's mouth, indicating either general poor attention to the mouth in the youngest listeners, or, potentially a developmental trend in focus to the speaker's articulators. Because previous research with adults has shown less visual influence on heard speech when visual attentional demands are increased (Alsius et al., 2005), it is possible that greater focus on the mouth exhibited with development reduces attention load during AV perception for children, which may facilitate more effective pickup of visual phonetic information with age. Either of these possibilities might provide some understanding of the relationship between gaze to the speaking face in developmental disability as well. For example, children with an ASD could be less generally attentive to the mouth of the speaker (also see Irwin and Brancazio, 2014) or may be exhibiting a more immature developmental pattern, which can be assessed by looking at the pattern of gaze in adolescents and young adults on the autism spectrum.

Although the previous literature indicates that young children differ from older children and adults in visual influence on heard speech (e.g., Hockley and Polka, 1994; Massaro, 1984; Massaro et al., 1986; McGurk and MacDonald, 1976; Sekiyama and Burnham, 2008), our behavioral data did not allow us to evaluate this finding in the current sample, primarily due to overall high performance in behavioral responding. An additional factor to consider is that the current stimuli were CV /ma/ and /na/'s. Connected speech, such as sentence-level stimuli, would be more akin to what many children and adults encounter in a communicative exchange. Future research should include somewhat more difficult visual tasks that would elicit a more variable pattern of results across participants, potentially with connected speech stimuli. Such work could determine whether age-related changes in looking to the face are linked with changes in AV perception, and in particular, whether this is due to a pickup of phonetic information or processing load.

ACKNOWLEDGMENTS

This work was supported by NIH Grant Nos. DC007339, DC011342, DC013864, and the LEARN Center at Haskins Laboratories. Thanks to Jon Close-Reilly for assistance with data coding and reduction and Amanda Sciola for help with editing.

Footnotes

1

We attempted to compare the age groups on their behavioral responses on the visual tasks. However, the comparisons were not informative due to overall high performance on the three conditions (visual only median: 100% correct; AV speech in noise median: 100% correct; McGurk median: 92% visually influenced responses). All but four participants had at least 90% accuracy in visual only and all but three had at least 90% accuracy in AV speech in noise.

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