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ORIGINAL RESEARCH
published: 07 February 2017

doi: 10.3389/fpsyg.2017.00106

Edited by:
Matthew William Geoffrey Dye,

Rochester Institute of Technology,
USA

Reviewed by:
Jacqueline Leybaert,

Université libre de Bruxelles, Belgium
Jerker Rönnberg,

Linköping University, Sweden

*Correspondence:
Mairéad MacSweeney

m.macsweeney@ucl.ac.uk

Specialty section:
This article was submitted to

Cognitive Science,
a section of the journal
Frontiers in Psychology

Received: 13 September 2016
Accepted: 16 January 2017

Published: 07 February 2017

Citation:
Pimperton H, Ralph-Lewis A and

MacSweeney M (2017)
Speechreading in Deaf Adults with

Cochlear Implants: Evidence
for Perceptual Compensation.

Front. Psychol. 8:106.
doi: 10.3389/fpsyg.2017.00106

Speechreading in Deaf Adults with
Cochlear Implants: Evidence for
Perceptual Compensation
Hannah Pimperton1, Amelia Ralph-Lewis1 and Mairéad MacSweeney1,2*

1 Institute of Cognitive Neuroscience, University College London, London, UK, 2 Deafness, Cognition and Language Centre,
University College London, London, UK

Previous research has provided evidence for a speechreading advantage in congenitally
deaf adults compared to hearing adults. A ‘perceptual compensation’ account of this
finding proposes that prolonged early onset deafness leads to a greater reliance on
visual, as opposed to auditory, information when perceiving speech which in turn
results in superior visual speech perception skills in deaf adults. In the current study we
tested whether previous demonstrations of a speechreading advantage for profoundly
congenitally deaf adults with hearing aids, or no amplificiation, were also apparent
in adults with the same deafness profile but who have experienced greater access
to the auditory elements of speech via a cochlear implant (CI). We also tested the
prediction that, in line with the perceptual compensation account, receiving a CI at
a later age is associated with superior speechreading skills due to later implanted
individuals having experienced greater dependence on visual speech information. We
designed a speechreading task in which participants viewed silent videos of 123 single
words spoken by a model and were required to indicate which word they thought had
been said via a free text response. We compared congenitally deaf adults who had
received CIs in childhood or adolescence (N = 15) with a comparison group of hearing
adults (N = 15) matched on age and education level. The adults with CI showed
significantly better scores on the speechreading task than the hearing comparison
group. Furthermore, within the group of adults with CI, there was a significant
positive correlation between age at implantation and speechreading performance; earlier
implantation was associated with lower speechreading scores. These results are both
consistent with the hypothesis of perceptual compensation in the domain of speech
perception, indicating that more prolonged dependence on visual speech information
in speech perception may lead to improvements in the perception of visual speech. In
addition our study provides metrics of the ‘speechreadability’ of 123 words produced in
British English: one derived from hearing adults (N = 61) and one from deaf adults with
CI (N = 15). Evidence for the validity of these ‘speechreadability’ metrics come from
correlations with visual lexical competition data.

Keywords: speechreading, deaf, cochlear implants, compensation, lipreading

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Pimperton et al. Speechreading in Deaf Adults with Cochlear Implants

INTRODUCTION

The perceptual compensation hypothesis refers to the idea
that sensory deprivation within one sensory modality will
stimulate compensatory perceptual improvement in another
sensory modality (Ronnberg, 1995). Individuals who are deaf
have compromised, and sometimes minimal, access to the
sounds that make up a spoken language via the auditory
modality. However, when a speaker produces speech, visual,
as well as auditory, information about speech sounds is
available to the observer. This raises the possibility that deaf
individuals may show spontaneous perceptual compensation in
the domain of speech perception, with their greater reliance
on the visual elements of speech in everyday life resulting in
superior speech perception skills in the visual-only modality. If
this perceptual compensation hypothesis is correct, we would
predict that deaf individuals would show superior speechreading
(visual-only speech perception) skills to hearing individuals
at a group level. However, evidence regarding whether there
exists a speechreading advantage for deaf individuals has been
mixed.

A body of work by Ronnberg et al. (1983) with individuals
who had acquired hearing loss in adulthood found no evidence
for superior speechreading skills in these adults compared
with hearing adults (Lyxell and Ronnberg, 1989, 1991). The
results of these studies led Ronnberg to conclude that “daily
dependence on lipreading in a variety of social situations
does not seem to suffice as a trigger for the development
of speech-reading skill” (Ronnberg, 1995). Tye-Murray et al.
(2007) examined speechreading of phonemes, words and
sentences in older adults with mild-moderate hearing loss
acquired in adulthood and compared their performance to
older adults without hearing loss. In a visual-only condition
they found no significant advantages for the adults with
hearing loss on phonemes or sentences, but did find that
they displayed a significant advantage over the adults without
hearing loss in terms of their visual recognition of single
words.

In contrast with the findings on adults with acquired hearing
loss, studies with groups of adults who have congenital or early
onset deafness have been more consistent in demonstrating
significant speechreading advantages compared to hearing adults.
Bernstein et al. (2000) examined the ability of adults with
normal hearing (N = 96) and with severe to profound early
onset (94% experienced onset ≤ 4 years) deafness (N = 72)
to speechread consonant-vowel nonsense syllables, words and
sentences. The adults with early onset deafness showed enhanced
speechreading ability relative to the hearing adults on all three
types of speechreading stimuli, indicative of superior visual
phonetic perception in the deaf adults. Auer and Bernstein
(2007) replicated this finding of a significant speechreading
advantage for adults with early onset deafness. They compared
the performance of a large group (N = 112) of adults with
early deafness (onset < 4 years) with that of a group of hearing adults (N = 220) on a sentence-level speechreading task. They found significant advantages for the deaf adults who identified 43.55% of the target words correctly compared to

only 18.57% for the hearing group. They concluded that “the
need to rely on visual speech throughout life and particularly
for the acquisition of spoken language by individuals with
early onset hearing loss, can lead to enhanced speechreading
ability.” Similar results were reported by Mohammed et al.
(2006) using the Test of Adult Speechreading, a speechreading
test that assesses speechreading skill at different levels of
linguistic complexity and that was designed specifically to give
deaf and hearing individuals an equal chance to demonstrate
their speechreading skill by not requiring spoken or written
responses. They found significant speechreading advantages for
a group of 29 profoundly deaf adults (age of onset < 5 years) over a comparison group of 29 hearing adults. In a study of Brazilian Portuguese-speaking adults, Oliveira et al. (2014) found similar advantages for deaf adults over hearing adults in terms of their performance on a range of speechreading tasks, and consistent advantages for those deaf adults with prelingual onset as compared to those with post-lingual onset.

A range of skills are likely to underpin this speechreading
advantage in those born deaf. In particular it is clear that
individual differences in cognitive skills play an important
role in speechreading skill (for review see Rönnberg et al.,
2013). For example, Rönnberg et al. (1999) reported a case
study of speechreading ‘expert’ – MM. They report that MM’s
speechreading skill was associated with high cognitive skills, such
as phonological skills and working memory capacity.

Better visual speech understanding in individuals with
congenital or early onset deafness, compared to hearing
individuals, but not in those with later onset of deafness is
consistent with work on perceptual compensation in blind
individuals. Gougoux et al. (2004) found superior pitch
discrimination skills in early blind adults (blinded < 2 years old) compared to sighted adults but no evidence of these enhancements to listening skills in late blind adults (blinded > 5 years old). They also reported a significant
negative correlation between age of blindness onset and pitch
discrimination performance, with those who were blind from
an earlier age showing superior performance on the pitch
discrimination task, and argued that “cerebral plasticity is more
efficient at early developmental stages” (Gougoux et al., 2004).
Subsequent studies have controlled for the influence of musical
experience by including sighted controls closely matched on
musical experience and have still provided consistent evidence
regarding the enhancement to pitch discrimination associated
with earlier onset of blindness (Wan et al., 2010).

Speechreading in Cochlear Implant
Users
In the majority of the studies reviewed above that demonstrated a
speechreading advantage in adults born severely to profoundly
deaf, the participants either used hearing aids or no hearing
device (Bernstein et al., 2000; Mohammed et al., 2006; Auer
and Bernstein, 2007). Thus, these individuals would have
had minimal access to the auditory speech signal meaning
that their dependence on visual speech to access spoken

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Pimperton et al. Speechreading in Deaf Adults with Cochlear Implants

language would have been high. Aparicio et al. (2012) have
demonstrated that this visual speech signal can be enhanced
by the use of cued speech (CS) which requires the user to
pay more attention to the lips. They tested deaf CS and non-
CS users and hearing participants on a sentence to picture
speechreading test. Deaf participants who were native CS users
were better speechreaders than deaf participants who were non-
CS users. Furthermore, the two groups of deaf participants
were better speechreaders than the hearing participants. This
study demonstrates that different language and communication
experiences in deaf individuals can lead to differences in
speechreading skill.

Another way to increase the clarity of the speech signal to a
deaf person is of course to increase access to the auditory input.
Over the last two decades increasing numbers of profoundly
deaf children and adults have received cochlear implants (CI);
devices which convert acoustic stimuli into electrical signals
and directly stimulate the auditory nerve to provide deaf
individuals with access to sound (American Speech-Language-
Hearing Association, 2004). For individuals who are congenitally
deaf but are implanted in early childhood, or for those who
receive a CI following an acquired hearing loss, it is often
the case that the CI gives them sufficient access to speech
sounds for them to be able to recognize speech in auditory-
only conditions, although there is considerable variability in
speech perception outcomes even within these populations
(American Speech-Language-Hearing Association, 2004). This
raises the question of whether the superior access to auditory
speech that deaf CI users experience impacts on their ability
to perceive visual speech. It is possible that a lesser degree
of dependence on the visual perceptual elements of speech
for understanding spoken language means that the group-
level deaf speechreading advantage may not be evident for CI
users.

However, it is important to recognize that a CI uses
a maximum of 22 electrodes to replace the function of
around 16,000 hair cells and as a consequence conveys highly
impoverished information about speech sounds compared to
a normally functioning human cochlea (Giraud et al., 2001;
Nittrouer et al., 2012). The reduced spectral information
conveyed by the CI is particularly problematic in terms of
its impact on auditory speech perception in the presence of
background noise (Srinivasan et al., 2013). This suggests that
despite the increased access to auditory speech that a CI can
bring, CI users might continue to make greater use of visual
speech information than hearing individuals and thus may
display a speechreading advantage.

The study by Oliveira et al. (2014) described above included
some deaf participants with CIs but they were grouped together
with participants without CIs, so it was not possible to
differentiate whether the individuals with CIs displayed a group
advantage relative to the hearing controls in terms of their
speechreading skills. A small number of studies have reported
data comparing speechreading skills of groups of deaf individuals
who have received a CI with hearing individuals. Rouger et al.
(2007) assessed speechreading performance in a group of post-
lingually deafened adults using a task in which participants

had to identify and repeat bisyllabic words presented in a
visual only format. The participants completed the assessment
both prior to receipt of a CI, immediately after switch on
and in the years subsequent to implantation. They found
that the deaf adults (N = 97) showed significantly higher
speechreading performance than a comparison group of hearing
adults (N = 163) when they were assessed prior to cochlear
implantation. This advantage maintained in the months and
years following cochlear implantation despite these deaf adults
substantially increasing their auditory-only word recognition
abilities. Additionally, Rouger et al. (2007) reported on a small
sample (N = 8) of participants who had experienced sudden
onset deafness less than a year before they received a CI and who
still showed significantly superior speechreading performance
compared to the hearing participants prior to, and following,
cochlear implantation. They argued on the basis of this that “a
high level of speechreading ability can be acquired rapidly during
a period of auditory deprivation,” a position in stark contrast to
that of Ronnberg (1995).

As part of a study looking at audiovisual spoken word
training, Bernstein et al. (2014) reported scores on a sentence-
level lipreading task (Auer and Bernstein, 2007) for a sample of
pre- or perilingually profoundly deaf adults (N = 28) with CIs,
the majority of whom received their CI in adulthood (>19 years),
and a sample of hearing adults (N = 43). As was the case in the
original Auer and Bernstein (2007) study, Bernstein, Eberhardt
and Auer found a significant advantage for the deaf group over
the hearing group in terms of their ability to identify words
from sentences presented in a visual-only format; the average
percentage words correct for the CI group was 39.4%, compared
to 8.1% for the hearing group.

Huyse et al. (2013) compared the performance of congenitally,
profoundly deaf children with CIs (N = 31; M age = 10 years,
SD = 0.47) with that of hearing children (N = 31; M
age = 10 years, SD = 0.5) on a task that required them to identify
vowel-consonant-vowel nonsense syllables. They reported no
significant differences between the groups in terms of their
identification performance when the syllables were presented in
a visual-only format, indicating no speechreading advantage for
these deaf children with CIs over their hearing peers. This finding
is consistent with the results from a study by Kyle et al. (2013)
which compared the speechreading skills of a more audiologically
diverse group of deaf children (severely to profoundly deaf, and
using CIs, hearing aids or no device) with those of hearing
children using a speechreading test that assessed visual speech
recognition at multiple levels of linguistic complexity (words,
sentences, and short stories). They found that the deaf and
hearing children performed very similarly on this test; there were
no significant differences between the groups on any of the three
subtests. It is possible that increased experience of and attention
to visual speech over a period of years is necessary for the
development of superior visual speech perception skills observed
in adults. Alternatively, it may be the case that the language skills
of deaf children limit their performance on speechreading tasks,
making it harder for them to demonstrate an advantage in their
visual speech perception skills than it is for deaf adults with more
experience of the spoken language the tests are conducted in.

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In this study we therefore focused on deaf adults and
aimed to test whether the group-level speechreading advantage
demonstrated by Rouger et al. (2007) in post-lingually deafened
adults who received their CIs in adulthood, and by Bernstein
et al. (2014) in pre- and perilingually deafened adults who
received their CIs in adulthood, could be replicated in a group
of congenitally deaf adults who received their CIs in childhood
or adolescence. We predicted that although these adults may
on average have experienced greater access to auditory speech
sounds than adults with equivalent levels of deafness without
CIs they would still have experienced, and be continuing
to experience, a much greater dependence on visual speech
information than hearing individuals and hence would show
evidence of perceptual compensation and demonstrate group-
level advantages in their speechreading skills compared to
hearing adults.

As mentioned above, auditory speech perception outcomes
following implantation are highly variable and are impacted by a
number of different variables. For post-lingually deafened adults,
factors identified as predictors of auditory speech perception
following implantation include duration of pre-implant deafness
and residual hearing pre-implant (Blamey et al., 1992; van Dijk
et al., 1999). For prelingually deaf children, age at implantation,
residual hearing pre-implant, non-verbal ability, and exposure
to an oral education have been identified as factors related to
variation in speech perception outcomes following implantation
(O’Donoghue et al., 2000; Svirsky et al., 2004; Geers et al., 2008).
Under the framework of perceptual compensation, it would be
predicted that individual variability in auditory speech perception
with a CI may relate to individual variability in visual speech
perception, with those individuals getting the least auditory
speech access via their CI relying the most on visual speech on
a day to day basis and hence showing the greatest enhancements
in their visual speech perception skills.

In the present study we focus on one variable that has
been consistently associated with variability in auditory speech
perception outcomes following CI; age at implantation. Age
at implantation effects on speech perception outcomes have
been discussed in the context of sensitive periods for the
development of the central auditory system. Sharma et al.
(2002) have argued that the first 3.5 years of life is a
period of maximal plasticity of the central auditory system.
They found evidence from electrophysiological recordings of
cortical auditory evoked potentials (CAEPs) that, for congenitally
deaf children, implantation after 3.5 years is associated with
an increased risk of developing atypical CAEPs following
implantation, with these atypical CAEPs particularly likely with
implantation after the age of 7 years (Sharma et al., 2002).
These findings suggest that receipt of an implant earlier in life
may be associated with better auditory speech perception as a
consequence of increased plasticity of the central auditory system.
Additionally, earlier recipients will also have experienced an
increased number of years accessing auditory speech via the CI
than later recipients. Taken together these factors may contribute
to earlier implanted individuals showing a reduced reliance on,
and therefore less well-developed, visual speech perception skills
than later implanted individuals.

One study has addressed this question of whether there
is evidence of a relationship between age at implantation
and speechreading ability and has done so in children with
CIs: Bergeson et al. (2005) compared the visual, auditory,
and audiovisual speech perception performance of a group of
earlier implanted (≤4 years 5 months) children with those
of a group of later implanted (>4 years 5 months) children
both before and in the years following implantation. They
found that overall the earlier implanted children showed better
speech perception performance than the later implanted children
when sentences were presented in auditory-only conditions,
but that this advantage was reversed when the sentences were
presented in visual-only conditions with the later-implanted
group showing superior performance in that context. These
findings in children with CIs are consistent with the perceptual
compensation hypothesis in indicating that a more protracted
period of deafness, with onset in early childhood, may be
associated with superior visual speech perception skills. In the
present study we sought to test this hypothesis in adults with CIs
who received their implant at highly variable ages (2–19 years).
The majority of children who are eligible for a CI today are now
receiving one before the age of 3 years (Raine, 2013) meaning
that opportunities to address questions about the implication
of variability in age of implantation that spans beyond the
sensitive period for the development of the central auditory
system are increasingly limited; thus this sample presents a
unique opportunity.

To summarize, in the present study we tested the following
hypotheses:

(a) Profoundly, congenitally deaf adults with CIs would show
a significant advantage in their single word speechreading
skills compared to a matched group of hearing adults.

(b) Within the group of adults with CIs, age at implantation
would relate to speechreading skill, with earlier implanted
adults showing less good speechreading skills.

MATERIALS AND METHODS

Participants
Sixty one native English-speaking hearing participants provided
data for this study. All reported normal hearing and normal
or corrected-to-normal vision. The participants were either
undergraduate students participating for course credit or
volunteers from the wider community who had responded to
adverts to take part in the study. All provided informed consent
prior to participation in the study. An additional 13 participants
consented to participate in the study but were excluded from the
current dataset as a result of not completing all items in the task.

Fifteen congenitally deaf participants with CIs participated
in this study. Age at implantation ranged from 2 to 19 years
(M = 8.27, SD = 5.05). All reported normal or corrected-to-
normal vision and profound deafness.

To faciliate comparisons between the speechreading
performance of CI and hearing participants, each of the
15 CI participants was individually matched to a hearing

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participant from the larger hearing sample (N = 61) on the
basis of age and education level, with these 15 matched hearing
participants forming the hearing comparison group (HCG).
There were no significant differences in the distribution of
ages between the CI (median = 23, range = 22–26) and HCG
(median = 23, range = 20–31) groups (U = 122, Z = 0.41,
p = 0.71, r = 0.07). The groups also did not differ significantly
in terms of the distribution of highest education level achieved
[χ2(2, N = 30) = 0.16, p = 0.92, ϕc = 0.07].

Materials and Procedure
One hundred and twenty three words were selected as the target
words for this experiment (see Supplementary Table S1 for full
list). All words were either concrete nouns or colors. Information
on the visual speech lexical competition experienced by the
speechread target words was sourced from the Phi-Lex database
(Strand, 2014). The measure used was a continuous measure
of visual lexical competition (ConV). This measure reflected
the overall competition in the reference lexicon for the target
word based on the similarity of the response distributions of its
constituent phonemes (from a forced choice visual only phoneme
identification task) to those of phonemes in every other word of
the same pattern type in the lexicon. For further details of how
this measure was derived, see Strand (2014). This variable was
available for 86 out of the 123 words in the study.

A video of each word being spoken by a female model was
made using a Sony Handycam (HDR-CX115). The word was
spoken aloud at a normal conversational volume during the
recording and the videos were subsequently edited to mute the
volume such that the participants saw a natural production of
the word but without any sound. The same model produced
each word. The model maintained a neutral facial expression in
the production of every word and the camera distance, lighting
and background conditions were consistent for each word (see
Figure 1).

Four different randomized orders of the 123 videos were
produced and participants were randomly assigned to complete
one of the four orders. The videos were presented using Opinio,
a web-based survey tool, and participants completed the task
via the internet on their personal computers. Participants were
instructed that they would see silent videos of a model saying a
single word and that they could only view each video once. They
were required to click to play each video and then write the word
they thought they had seen in a free text response box before
moving onto the next video.

When scoring the responses as correct or not relative to
the target, participants were given one point for an item if
the response either directly matched the target or if they had
produced a homophone of the target (e.g., had written ‘I’ for the
target ‘eye’). This meant they could score a maximum of 123 on
the task.

Prior to completing the speechreading task the participants
provided demographic information via the web-based tool.
Additional audiological information was collected from the
participants with a CI via a paper-based response form prior to
their completion of the speechreading task.

FIGURE 1 | Screenshot of visual speech model who produced all
stimuli.

RESULTS

Overall Speechreading Performance of
Hearing Participants
The mean number of words identified correctly by the 61 hearing
participants was 22.38 (SD = 9.94; range = 2–48) out of 123. This
was equivalent to a mean proportion correct of 0.18 (SD = 0.08;
range = 0.02–0.39). The mean number of words identified
correctly by the hearing participants was significantly above the
floor of 0 [t(60) = 17.56, p < 0.001, d = 2.25] and significantly below the ceiling of 123 [t(60) =−79.08, p < 0.001, d =−10.12].

Comparison of Speechreading
Performance for the CI Participants and
the Hearing Control Group (HCG)
The mean number of words identified correctly by the CI
participants was 40.80 (SD = 16.81; range = 9–62) and by
the matched HCG was 24.20 (SD = 10.40; range = 4–46) (see
Figure 2). This was equivalent to a mean proportion correct
of 0.33 (SD = 0.14) for the CI group and 0.20 (SD = 0.08)
for the HCG. Levene’s test indicated unequal variances between
the two groups. Therefore the unequal variance Welch t-test

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FIGURE 2 | Mean number of items correctly identified by the Cochlear Implant participants (CI) and the hearing control group (HCG). N = 15 in each
group.

was used. This showed that deaf CI users scored significantly
higher than the hearing control group on the speechreading task,
t(23.35) = 3.25, p = 0.003, d = 1.19. The mean number of items
correct for the matched HCG used for this group comparison
(N = 15; M = 24.20, SD = 10.40) did not differ significantly from
that of the remaining hearing participants (N = 46; M = 21.78,
SD = 9.83), [t(59) = 0.82, p = 0.42, d = 0.24], suggesting that
the level of performance of these matched hearing participants
was representative of the performance level of the wider hearing
sample.

Relationship between Speechreading
Performance and Age at Implantation
Within the CI group there was a significant positive correlation
between age at implantation and score on the speechreading
task (r = 0.61, p = 0.02, 95% CI = 0.29–0.84), with those
participants who received their CIs at a later age showing higher
speechreading scores than the earlier implanted participants (see
Figure 3). A regression analysis predicting speechreading task
score with age and education level entered at Step 1 and age
at implantation at Step 2 indicated that age at implantation
accounted for significant unique variance in speechreading
performance, accounting for 30% of the variance over and above
the 11% accounted for by age and education level (Table 1).

Individual Item Accuracy and
Relationship with Word Properties
For the 61 hearing participants, the proportion correct for
individual items ranged from 0.77 (for ‘rabbit’) to 0.00 (for

‘bull’; ‘duck’; ‘fan’; ‘jacket’; ‘mat’; ‘milk’; ‘shorts’; ‘skirt’; ‘trousers’;
‘van’; ‘wall’; ‘wheel’). Supplementary Table S1 presents data on
the proportion correct responses for each of the 123 items
individually for the hearing sample (Supplementary Table S1).
These data provide a metric of ‘speechreadability’ of the 123
words when produced in British English.

There was a high degree of concordance between the hearing
participants and the deaf participants in terms of the relative
success rates on the individual items [r(121) = 0.79, p < 0.001, BCA bootstrapped 95% CI = 0.70–0.85]. For the 15 deaf participants with CIs, proportion correct for individual items ranged from 0.87 (for ‘elephant’; ‘fish’; ‘lorry’; ‘orange’; ‘phone’; ‘rabbit’) through to 0.00 (for ‘ball’; ‘bee’; ‘bull’; ‘duck’; ‘fan’; ‘hand’; ‘hen’; ‘ladder’; ‘mat’; ‘milk’; ‘pan’; ‘peg’; ‘red’; ‘ring’; ‘shorts’; ‘wall’; ‘wheel’; ‘wing’). Supplementary Table S2 presents data on the proportion correct responses to each of the 123 items for the participants with CIs.

Relationships between the proportion of correct responses
to an item (PropCorr) and word properties of that item were
examined for the 86 words that had continuous visual lexical
competition data (ConV) available for them. The distribution
of the PropCorr and ConV variables showed deviations from
normality so bias corrected and accelerated bootstrapped 95%
confidence intervals (1000 bootstrap samples) are presented for
the correlation coefficients. The number of correct responses for
the items showed a significant negative correlation with ConV
for both the hearing participants [r(84) =−0.39, p < 0.001, BCA bootstrapped 95% CI =−0.55 to −0.18] and the CI participants [r (84) =−0.50, p < 0.001, BCA bootstrapped 95% CI =−0.64 to −0.34] indicating that words that had fewer visual (visemic)

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FIGURE 3 | Correlation between age of cochlear implantation in the deaf participants and number of visual speech words correctly identified.

lexical competitors were more successfully identified by both
groups of participants.

DISCUSSION

The first aim of this study was to compare the single word
speechreading ability of hearing adults and deaf adults with CIs
in order to test the hypothesis that prelingually deaf adults who
received an implant in childhood or adolescence would show
a speechreading advantage. We found that the mean score on
the speechreading task was significantly higher for the adults
with CIs than for the matched comparison group of hearing
adults. The performance of the matched HCG did not differ
significantly from that shown by the larger sample of hearing
participants who were not selected for the HCG, suggesting HCG
performance was representative of the broader hearing sample.
This finding of a speechreading advantage for the deaf adults with
CIs in this study is consistent with the findings of Rouger et al.
(2007) and Bernstein et al. (2014) who found evidence of a deaf
speechreading advantage for adults with later age at implantation
or later age at onset of deafness. These consistent findings in
adults with CIs suggest that even with the greater access to the
auditory elements of speech that a CI provides, these adults
are still substantially more dependent on visual speech than
hearing adults and consequently have developed compensatory
superiority in their ability to use visual speech information to

understand spoken language. It would be interesting in future
studies to contrast this group with deaf adults without CI to
further understand the extent of this compensation.

In terms of the locus of this compensation, the finding in
this study of an advantage for the adults with CIs on a single
word speechreading task in which there was no sentential context
suggests that the deaf speechreading advantage is not exclusively
driven by an enhanced ability to use sentence-level contextual
information to facilitate identification of individual words. This
is not to say that the use of top down sentence-level processing

TABLE 1 | Results of regression analyses predicting speechreading score
with age and education level entered at Step 1 and age at implantation at
Step 2.

R2 R2 change F change (p) Final standardized
β (p)

Step 1
Age
Education level+

0.11 0.11 0.77 (0.49)

Step 2
Age
Education level+

Age at implantation

0.41 0.30 5.51 (0.04) 0.001 (0.99)
0.196 (0.50)
0.56 (0.04)

+Dichotomised into < or ≥ undergraduate degree. Age at implantation accounted for unique variance in the speechreading score.

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to aid speechreading is not something that deaf adults develop
the capacity to use to effectively support speechreading in real
word contexts, but rather that they also have enhanced skills
in domains that support the type of context-free lipreading
performance assessed in this task. This suggests that they may be
better at visually perceiving individual phonemes. Alternatively,
they may be better either at perceiving rapid sequences of
phonemes or at using coarticulatory information in phoneme
sequences to disambiguate visual phonetic information (e.g.,
influences of voiced vs. voiceless consonants on preceding
vowel length; although the phonemes /t/ and /d/ are visually
perceptually identical in isolation they have a differential effect
on the articulation of the middle vowel when in a word final
position; contrast ‘beat’ and ‘bead.’) Future studies should aim to
test this by comparing the performance of hearing adults and deaf
adults on a speechreading task in which they have to speechread
both individual phonemes (e.g., ‘/f/’) and also non-words which
use the phonotactics of the ambient spoken language (e.g., ‘mip,’
‘niddy’).

The second aim of this study was to test the hypothesis that,
within the CI group, later implantation would be associated with
superior speechreading skills. We found a significant positive
correlation between age at implantation and speechreading
performance, indicating a speechreading advantage for those
implanted at later ages. This result is consistent with the
hypothesis that a greater duration or degree of dependence on
visual information for speech perception leads to improved visual
speech perception skills and therefore with the idea of perceptual
compensation in the domain of speech perception. The finding
of superior visual speech perception skills in later implanted
adults is also consistent with the findings of Bergeson et al.
(2005), who reported superior visual-only speech perception in
later-implanted children (in contrast to superior auditory speech
perception skills in earlier-implanted children). However, it is
important to acknowledge this was a preliminary study in adults
with CIs with the small sample size meaning that the confidence
intervals for this correlation are wide and therefore replication
of this result in a larger sample would be of value. A further
limitation of this study was the lack of detailed audiological
information available for the CI participants. We had no objective
audiological measures for the CI users. Thus it was not possible
to determine whether the earlier-implanted participants did have
superior auditory speech perception through their implant than
the later-implanted participants, as was the case in the Bergeson
et al. (2005) study with children, and whether this related to their
visual speech perception skills.

It was also the case that we did not have extensive information
regarding the language skills of the CI participants. It is possible
that variability in underlying spoken language knowledge within
the CI group may have influenced their performance on the
speechreading task and hence the relationship between age at
implantation and speechreading score. However, this would be
dependent on the later implanted participants showing superior
spoken language skills to the earlier implanted participants,
a situation which is the reverse of that typically observed.
Additionally, the language demands in this speechreading
task were relatively low. Participants identified single words,

all of which were early acquired concrete nouns, meaning
that the contributions of existing language knowledge to task
performance are likely to have been minimized.

The speechreading task used in this study was completed
remotely via the internet. Unfortunately this meant that we were
unable to collect measures of participant’s other cognitive skills
known to be important to individual differences in speechreading
skill, such as phonological skills and working memory capacity
(see Rönnberg et al., 1999, 2013). Future studies should attempt
to include these measures. Remote data collection also meant
that we were unable to monitor participants’ attention while
they undertook the task. We reasoned that if participants
showed item-level response patterns that were consistent with the
predictions of models of spoken word recognition in the visual
modality, this would support the validity of this task as a measure
of speechreading. Activation-competition models of spoken word
recognition in the auditory modality (e.g., the Neighborhood
Activation Model; Luce and Pisoni, 1998) have posited that
hearing a spoken word elicits simultaneous activation of multiple
words in the mental lexicon that are perceptually similar to the
target word and compete with the target word for recognition, the
result being that words with more perceptually similar ‘neighbors’
are recognized with less accuracy than words that have fewer
such neighbors in auditory word recognition paradigms (Dirks
et al., 2001). Analogously, research examining spoken word
recognition in the visual modality has shown equivalent effects
of visual lexical competition experienced by the target word
on recognition accuracy suggesting that activation-competition
models of word recognition extend beyond the auditory modality
(Feld and Sommers, 2011; Strand and Sommers, 2011). For
both the CI and hearing groups in the present study, visual
lexical competition showed a significant negative relationship
with recognition accuracy for the words; those words with
greater visual lexical competition were correctly recognized less
often than those with lower visual lexical competition. This
suggests that the single word speechreading task was measuring
a consistent construct across the two participant groups, and
supports the validity of this task as a measure of visual speech
perception.

CONCLUSION

The results of this small scale study provided two strands of
evidence that are consistent with perceptual compensation in
the domain of speech perception. First, prelingually deaf adults
with CIs showed a significant advantage in terms of their
performance on a visual-only speechreading task compared to
a comparison group of hearing adults matched on age and
education. Second, age at implantation within the CI group
showed a significant positive relationship with performance on
the speechreading task; participants who received their implants
later in life showed superior visual-only speech perception skills.
We argued that in both cases these patterns of findings resulted
from increased dependence on visual speech information leading
to compensatory improvements in perception of speech via the
visual modality.

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ETHICS STATEMENT

This research was approved by the University College London
Research Ethics Committee. Online informed consent was
obtained from each participant.

AUTHOR CONTRIBUTIONS

HP and MM designed the study. AR-L collected the data. HP
analysed the data. HP and MM wrote the paper.

FUNDING

This research was supported by a Wellcome Trust Senior
Research Fellowship (grant number 100229/Z/12/Z) awarded to
MM.

SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found
online at: http://journal.frontiersin.org/article/10.3389/fpsyg.
2017.00106/full#supplementary-material

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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.

Copyright © 2017 Pimperton, Ralph-Lewis and MacSweeney. 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 original 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.

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• Speechreading in Deaf Adults with Cochlear Implants: Evidence for Perceptual Compensation

Introduction
Speechreading in Cochlear Implant Users
Materials And Methods
Participants
Materials and Procedure
Results
Overall Speechreading Performance of Hearing Participants
Comparison of Speechreading Performance for the CI Participants and the Hearing Control Group (HCG)
Relationship between Speechreading Performance and Age at Implantation
Individual Item Accuracy and Relationship with Word Properties
Discussion
Conclusion
Ethics Statement
Author Contributions
Funding
Supplementary Material
References

Summary of the Essay Assignment for PSYC 1001

Each student will write an essay reviewing one empirical study in psychology. Complete instructions are in the Essay Instructions learning module. The grading rubric explains exactly how these essays will be graded. Please refer to it. The power point presentation gives more details about the assignment and tips to doing it. Please review it. The sample essay is an example of how a perfect essay would appear. Please read over it.

Instructions Summary

For each essay a student will:

1. Locate a research article (see steps for locating an article) in the field of psychology that:

is peer-reviewed,

reports an original empirical study (no meta-analyses or literature reviews),

has a “Methods” or “Procedures” section, and

is located in the UC library.

1. Have the article approved by the instructor:

after finding the article, email me the citation (without an attached pdf) using the library’s citation page for the article.

my email is

hamburmh@ucmail.uc.edu

.

within 2 days I will email back approving the article or asking you to find a new article.

you may need (or choose) to find a new article if the first one is not a good fit.

2. Complete 2 prewriting assignments that have students locate the information in their article that must be included in the essay.

The first prewriting assignment (EI PW1) is worth 50 points and requires students to identify from the article they found in the UC library:

i. The APA citation copied and pasted from the UC library website;

ii. The authors of the article who conducted the research and wrote the article;

iii. The year that the article was published;

iv. The title of article;

v. The name of the journal that published the article;

vi. The page numbers in the journal that the article appeared on;

vii. The purpose that motivated the research study;

viii. The theory (stated as IV affects DV) tested by the study;

ix. The number, species, and other important characteristics of the subjects who provided the data for the study;

x. A control variable that is the same for all subjects in the study;

xi. A possible confounding variable that could mess up the results of the study if it is not controlled; and

xii. A reason that the research is important or is not important.

The second prewriting assignment (EI PW2) is worth 50 points and requires students to identify from the article they found in the UC library:

xiii. The independent variable (IV) in the theory;

xiv. One way that the IV is operationalized so that it can be measured in the study;

xv. Any control group who got 0 of the IV;

xvi. The dependent variable (DV) in the theory;

xvii. One way the DV is operationalized so that it can be measured in the study;

xviii. The one specific hypothesis tested with the operationalized IV and operationalized DV stated above;

xix. The design (how data was collected) used in the study;

xx. The data that confirm or do not confirm the specific hypothesis stated above;

xxi. The p-value computed by the statistics and if the hypothesis is confirmed or not; and

xxii. How ethically the subjects were treated by the researchers.

3. After satifactorily completing both prewriting assignments, students will write a 500-600 word essay (see rubric for grading criteria) that includes:

the full citation with author(s), year published, title, journal name, and page numbers;

the purpose or theory motivating the research study;

one (and only one) of the specific hypotheses tested in the study;

the subjects for the study giving the number and species as a minimum;

the research methods (design) used including how the independent variable (IV) and dependent variable (DV) in the chosen specific hypothesis were measured;

the variables that apply to the one chosen specific hypothesis including:

i. the one independent variable and how it is operationalized,

ii. the one dependent variable and how it is operationalized, and

iii. a control or confounding variable;

numerical results from the data reported in the article that apply to the one chosen specific hypothesis (looking in a table is often necessary);

the conclusion of the researchers to confirm or not confirm the hypothesis;

the student’s own opinion of the ethics for the study including reasons; and

the student’s own evaluation of the importance of the research including reasons.

4. Essays must:

be typed double spaced, using12-point font and 1 inch margins;

use correct spelling, grammar, and punctuation;

include student’s name, assignment due date, and page number on every page; and

be submitted on Canvas in the correct dropbox under “Assignments”.

5. Essays will be graded within 3 weeks of the due date and then students will have at least 1 week in which they may revise their essay if they choose.

Essays and revisions will be graded using the rubic on the next page.

Revisions are optional, but cannot be submitted late.

The final grade will be average of initial essay grade and the revision grade if students do a revision. Otherwise the initial grade stands.

Essays and prewriting assignments are turned in electronically on Canvas:

First prewriting EI PW1 is due February 24 at 4pm and the second EI PW2 is due February 26 at 4pm.

Students may have to redo the prewriting assignments if they do not complete it successfully (score at least 40 out of 50) the first time.

Essay is due on March 11 at 4pm, revision due April 29 at 4pm.

Late first submission for prewriting or essays will be penalized 10 percent. If the first submission for an essay is more than 5 days late, it may not be graded in time to revise. Late revisions are not accepted.

Essays must be submitted in the correct drop box under “Assignments” on Canvas using MSWord “ x” format.

Complete detailed instructions for the essays, including the grading rubric, are in the “EI (Essay Instructions): Research on the Mind” learning module.

Essay Grading Rubric for Introduction to Psychology

Excellent
(10 pts)

Good
(8-9 pts)

Adequate
(6-7 pts)

Attempted Fair
(4-5 pts)

Attempted Poor (2-3 pts)

Not apparent
(0-1 pts)

Clarity of writing

No errors in sentence structure, quotes, spelling, or grammar

A few errors but meaning is clear

Several errors; some that interfere with meaning

Several errors that interfere with meaning

Many errors that interfere with meaning

Essay is difficult to understand because of errors

Citation

All 5 elements correct (authors, title, date, journal, & page numbers)

At least 4 elements correct including authors, date, and title

Authors, date, and title correct

Little citation information given, but article can be identified

Inadequate citation to locate article

No citation given

Theory / purpose

Purpose of study and theory tested clearly stated

Purpose or theory stated although may be vague

Purpose or theory alluded to, but not clearly stated

Some mention of the purpose of the study

Purpose and theory incorrect

No purpose or theory stated

Hypothesis

1 specific hypothesis clearly stated with operationalized IV and DV

Hypothesis stated but not tied to theory or variables

Hypothesis vague or unclear

Incorrect hypothesis

Hypothesis fails to relate to topic

No hypothesis

Design

Research design clearly described including how IV & DV measured

Research design described but how IV or DV measured not clear

Some aspects of research design described but vague and unclear

Little research design described

Incorrect research design described

No research design described

Subjects

Number, species & some descriptive information for subjects given

Number & species of subjects stated clearly but no other information

Either species or number of subjects not stated

Some discussion of subjects, but no number or species stated

Little discussion of subjects

No discussion of subjects

Variables

IV, DV, and a confound or control clearly identified

IV and DV accurately identified

IV or DV accurately identified

IV & DV incorrect, but some understanding of variables shown

Variables incorrectly identified

No identification of variables

Results

Results w/ statistics and if hypothesis confirmed clearly stated

Results stated w/o statistics but clearly indicate if hypothesis confirmed

Results given but not tied to IV, DV, hypothesis, or theory

Results not correctly stated or incorrectly tied to theory

Only vague statement about results

No results given

Ethics

Student’s opinion of the ethics and reasoning clearly stated

Student’s opinion of the ethics clearly stated but no reason given

Ethics discussed generally but student’s opinion not expressed

Ethics discussed generally but not specific to the study

Ethical issue incorrectly specified

Ethics not addressed

Evaluation

Student’s appraisal of the importance of research & reason clearly stated

Student’s appraisal of the importance of research stated wi/o reason

Statement about importance of the research copied from authors

Discussion of the application of the research but no appraisal provided

Appraisal unclear and no reason given

No appraisal of importance of the research