1

Taitelbaum-Swead, R., Avivi, M., Gueta, B., Fostick, L. (2019). The effect of

delayed auditory feedback (DAF) and frequency altered feedback (FAF) on speech

production: cochlear implanted versus normal hearing individuals. Clinical

Linguistics & Phonetics.

***This is a self-archiving copy and does not fully replicate the published

version***

The Effect of Delayed Auditory Feedback (DAF) and Frequency Altered Feedback

(FAF) on Speech Production: Cochlear Implanted vs Normal Hearing Individuals

Running Title: Auditory Perturbation in CI and NH

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Abstract

Normal auditory feedback contributes to moment to moment control of speech

production. Effects of auditory feedback’s absence on hearing-impaired individuals

are widely documented but auditory perturbation has not been investigated. Our

objective was to evaluate the effect of Delayed Auditory Feedback (DAF) and

Frequency Altered Feedback (FAF) on speech production among prelingual cochlear

implant (CI) users and normal hearing (NH) individuals, to evaluate CI users’ reliance

on auditory feedback. Twenty young adults (10 CI, 10 NH), without developmental

and cognitive impairments, participated in the study. Under variable auditory

feedback conditions, speech production (spontaneous or reading aloud) was measured

using speech rate, percentage of interruptions, fundamental frequency (F0), and

relative intensity. Results showed that: (1) Both DAF and FAF caused slower speech

rates and more interruptions while reading aloud, with DAF having larger effect, (2)

Altered feedback produced no differences between groups, except an increase in F0

for CI users during DAF, and (3) CI users’ ability to understand speech via phone and

without lip-reading was positively correlated with performance under DAF. These

findings suggest auditory perturbation similarly affects speech production among

prelingual CI users and NH individuals, indicating CI users depend on auditory

feedback to the same degree as normal hearing individuals.

Key words: speech production, Delayed Auditory Feedback, Frequency Altered

Feedback, auditory perturbation, cochlear implants

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Introduction

Many speech perception theories presuppose a tight link between speech

perception and production (Liberman, Cooper, Shankweiler, & Studdert-Kennedy,

1967). This presupposition has been strengthened by neurobiological evidence.

Transcranial magnetic stimulation of the motor cortex has shown activation of

speech-related muscle areas during speech perception (Fadiga, Craighero, Buccino, &

Rizzolatti, 2002). In addition, fMRI studies have shown overlapping activated cortical

areas during speech production and passive listening to speech (Wilson, Saygin,

Sereno, & Iacoboni, 2004).

Further supporting the proposed speech perception/production association is

evidence gathered from studying the absence of auditory feedback on speech

production. There is compelling evidence that absence of auditory feedback during

language acquisition affects the development of speech production abilities (Blamey

et al., 2001). Among adults that have already acquired speech, the absence of auditory

feedback is also impactful, but in a different way (Goehl & Kaufman, 1984): It is

associated with deterioration in speech production over time. Studies that examined

the deterioration of segmental and supra-segmental features of speech in

adventitiously deaf adults ( Lane & Webster, 1991) found that the absence of auditory

feedback (due to losing the ability to hear) affected the accuracy of the acoustic-

phonetic features of some speech sounds such as vowels, voiced and voiceless

consonants (Waldstein, 1990), and substitution of affricates and fricatives (Leder &

Spitzer, 1990). At the supra-segmental level, adventitiously deaf individuals showed

changes in fundamental frequency, increases in voice intensity, and lengthening of

speech utterances (Leder & Spitzer, 1993). These changes caused their speech to

deteriorate further with time.

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Auditory feedback affects speech not only when it is absent, but also when it

is altered. Studies have examined the effect of immediately altered auditory feedback

on speech production of normal hearing adults. These alterations included: Adding

background noise known as the Lombard effect (Lane & Tranel, 1971), Frequency

Alteration Feedback (FAF), (Elman, 1981), and delayed auditory feedback (DAF)

(Fairbanks & Guttman, 1958). These studies also found changes in speech production

as a result of altered feedback.

Among the variety of techniques for altering auditory feedback, Delayed

Auditory Feedback has been the most extensively studied technique for its effect on

speech production. As early as 1950, it was already reported that when a subject hears

himself with a DAF, he decreases his speech rate and fluency of speech, and increases

vocal intensity (Fairbanks & Guttman, 1958). In specific, a delay of 200 ms has been

reported to have a maximum negative effect on the speaker: This length delay

approximately matches the average syllable length, thus creating an interfering,

disruptive rhythm that makes monitoring the speech signal difficult for the listener

(Fairbanks, 1955). After these pioneering findings, many subsequent studies found

changes in speech production resulting from DAF. These changes include slowing of

the speech rate, prolongations of vowels, disfluencies and misarticulations

(Sasisekaran, 2012). These speech disruptions are thought to be corrective actions to

overcome the discrepancies between intended output and conflicting sensory

feedback.

Another type of auditory perturbation, FAF, in which the voice pitch is

unexpectedly shifted upward or downward and presented to the speaker while

speaking (Behroozmand, Korzyukov, Sattler, & Larson, 2012), also creates disruption

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in speech production. Variations in the direction of fundamental frequency (F0) as a

result of pitch perturbation is reported in the literature (Petersen, 1986). Usually,

talkers show a compensatory pattern: When the perceived pitch is higher than the

intended pitch, the talker decreases F0 in order to compensate for the disparity.

Conversely, when the feedback pitch is downward, the F0 is increased (Behroozmand

et al., 2012). However, some talkers change their pitch in the same direction as the

feedback, thus making the F0 more distant from the original value (Jones & Munhall,

2003). The FAF technique is a useful method to directly investigate the relationship

between auditory feedback and pitch control during ongoing vocalizations.

While many of the previous studies examined the impact of altered auditory

feedback on normal hearing individuals, less attention has been paid to the impact on

those with cochlear implants. A large number of studies have demonstrated the

success of cochlear implants in providing better sound accessibility and enabling

better speech perception and production, among both children and adults (De Raeve,

Vermeulen, & Snik 2015; Svirsky, Robbins, Kirk, Pisoni, & Miyamoto 2000). The

literature has also shown evidence that speech production accuracy is closely related

to speech perception abilities in cochlear implants (CI) users. Studies found that early

speech intelligibility is strongly correlated with speech perception and language

abilities (Blamey et al., 2001; Tobey, Geers, Brenner, Altuna, & Gabbert, 2003).

Moreover, speech production proficiency also serves as a significant predictor of

development in speech perception and language skills after 10 years of CI use

(Casserly & Pisoni, 2013; Tobey, Geers, Sundarrajan, & Lane, 2011). Testing CI

users of different ages and onsets of deafness (such as prelingual children, prelingual

adults, and postlingual adults) can show how restored hearing affects speech

production differently among these groups (Blamey et al., 2001; Kishon-Rabin,

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Taitelbaum, Tobin, & Hildesheimer 1999; Tobey et al., 2003). Longitudinal studies

have reported improvements in segmental and supra-segmental aspects of speech,

such as shifts in various acoustic and perceptual variables, generally toward the range

of normal (Kishon-Rabin et al., 1999; Svirsky, Jones, Osberger, & Miyamoto 1998;

Tye-Murray, Spencer, & Woodworth 1995). Some studies evaluated the short-term

effect of CIs on speech production of the hearing-impaired by turning off the CI in

order to remove auditory feedback (Lane et al., 2007; Svirsky et al., 1998); the

absence of auditory feedback resulted in speech production changes in vowel

formants (Lane et al., 2007; Svirsky & Tobey, 1991), nasalization (Svirsky et al.,

1998), production of sibilants (Lane et al., 2007), fundamental frequency and intensity

(Higgins, McCleary, & Schulte, 2001). These short-term effect studies suggest that CI

recipients who demonstrate better speech perception and production as a result of CI

usage may be relying on moment to moment auditory feedback, which could explain

the immediate deterioration of some speech contrasts when the CI is turned off (Lane

et al., 2007; Svirsky & Tobey, 1991). In an interesting study, Casserly (2015)

simulated the experience of hearing using a CI with normal hearing (NH) listeners.

Using this simulation, they evaluated the effect of real-time CI auditory feedback on

speech production in NH subjects, and found significant changes in the first formant

(F1) of vowels. This finding may reflect strategies to maximize kinesthetic feedback.

While the impact of the absence of auditory feedback on CI users is well-

established, the effect of auditory perturbations is less well-studied. The effect of

DAF has been compared utilizing individuals with different types of hearing

impairments (Barac-Cikoja, 2004; Tye-Murray, 1992); CI users were found to be

affected by DAF differently than participants with hearing aids, as were prelingual CI

children compared to postlingual CI children. However, these studies were limited by

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the fact that none of these groups were compared to normal hearing participants. A

study that did, compare postlingual CI users to a normal hearing group, used a

variation of the Lombard effect, testing the impact of adding different levels of

background noise on speech production (Perkell et al., 2007). They found that sibilant

contrasts were susceptible to noise. These sibilant contrasts decreased over the entire

range of increasing noise levels for NH and was variable for CI users. Moreover, CI

users were less able to increase contrasts during noise, compared to their NH peers.

The results of this study suggest that CI users rely on auditory feedback differently

than NH individuals. However, the manipulation was subjected only to the addition of

background noise. Therefore, it is still unknown whether prelingual CI users will be

sensitive to altered temporal and spectral auditory feedback, compared to normal

hearing participants.

The current study

To our knowledge, this is the first study to evaluate the effect of altered

auditory feedback on speech production of prelingual CI user adults compared to NH

adults. This study paradigm enabled us to test whether CI users that were implanted

early in their life, rely on auditory feedback to the same degree as their NH peers,

shedding light on the role of hearing in speech production among adults.

From a clinical perspective, this paradigm is an additional method to measure

the reliance on auditory feedback provided by the CI. In order to estimate how much

this reliance on auditory feedback is currently reflected in day to day life, we asked CI

participants about their functional hearing (understanding speech via phone, without

lip-reading, and in multiple-speaker situations). We set out to analyze the correlation

between this self-assessment of functional hearing and the speech production that

8

would occur as a result of altered feedback. This correlation was expected to give

further insight into the nature of the relationship between the clinical measurements of

the impact of auditory feedback and the subjective impression of its role in day-to-day

life. The results of the current study are anticipated to shed light on the extent of the

relationship between speech perception and production among CI users.

Method

Participants

Two groups of subjects were enrolled in the study: Individuals with CIs and

those with normal hearing. All were native Hebrew speakers and had no

developmental and cognitive impairments.

CI users

The CI group consisted of 10 implanted young adults (8 women and 2 men)

who met the following inclusion criteria: (1) onset of severe to profound hearing

impairment before 3 years of age; (2) hearing aid usage prior to implantation; (3)

mainstream education and oral communication; and (4) usage of multichannel

cochlear implants. The mean chronological age of the CI group, their hearing devise,

age at implantation, etiology of hearing loss, and type of implant are described in

Table 1.

INSERT TABLE 1

NH participants

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The NH group consisted of 10 young women (n=8) and men (n=2),

undergraduate students aged 20-25 years, who had normal hearing thresholds pure-

tone air-conduction thresholds less than 15 dB HL bilaterally at octave frequencies

from 250 - 4,000 Hz.

Task and stimuli

The stimuli were delivered in 70 dB SPL under three different conditions: (1)

Normal Auditory Feedback (NAF)- a natural condition (for NH) and with the implant

on (for CI); (2) Delay Auditory Feedback (DAF) – delay of 200 milliseconds (found

to be most impactful on speech production) with no change in spectral characteristics

of the speech; (3) Frequency Altered Feedback (FAF) – Increase of 200 cents (0.167

octaves) in F0 with no change in temporal characteristics of the stimuli

(Behroozmand et al., 2012). Stimuli consisted of: (1) reading aloud from three

different passages (one for each condition) of 180-200 syllables that included all

consonants and vowels in the Hebrew language, and (2) spontaneous speech – the first

fifteen seconds of participants’ answers to everyday questions delivered by the

researchers (three questions- one for each condition: Describe your living

environment, the route from your home to the nearest grocery store, and your job).

The CI participants also answered three questions about their subjective level

of functioning with the implant in daily activities. The questions asked about the CI’s

hearing ability (1) via phone, (2) listening to speaker in the same room, but without

the availability of lip-reading (such as when not seeing the speaker), and (3) in a

conversation with multiple talkers. Each question was answered on a 1-4 scale.

Apparatus

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Auditory perturbation was done using application developed by Kosti. This

application implemented delayed auditory feedback with a scale unit of milliseconds

and fundamental frequency changes of semitones (100 cents). The application was

operated by a mini Ipad 2013. The stimuli were delivered to the NH group by insert

earphones for the Ipad and to the CI group by a mobile induction hook (music and

mobile) connecting to the CI with electromagnetic telecoil. Recordings were done

using a Sennheiser MZH 3072 microphone positioned 10 cm from the speaker’s

mouth and external sound card (Asus Xonar U7). All recordings were saved onto a

laptop (Dell). Recordings were edited using Sound Forge 11 software which digitized

(16-bit) the stimuli at a sampling rate of 44 kHz and all acoustic analyses were done

by Praat software.

Acoustic Analyses

Speech rate was determined by calculating the number of syllables spoken per

second, divided by the length of the passage in seconds; silent pauses were not

included. In addition, the number of interruptions was also calculated: Including

omissions, substitutions and duplications of syllables or words. The number of

interruptions was divided by the number of syllables per condition.

The fundamental frequency and the relative intensity were measured only

during the reading of passages. A fundamental frequency extraction algorithm, a

built-in feature of the Praat program based on an autocorrelation function, was used to

estimate the mean F0. Mean relative intensity was calculated automatically by the

Praat software.

Procedure

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The study was approved by the Institutional Review Board and was conducted

in accordance with Good Clinical Practice (GCP) guidelines. All participants received

a full explanation about the study and signed an informed consent document. All

potential candidates for the NH group were screened for hearing levels prior to

participation in the study.

Participants were required to read a passage and to answer the everyday

questions. The order of the conditions and the order of the speech stimuli (reading

passage and spontaneous speech) were randomly intermixed across participants. Each

participant was recorded under the three different conditions (NAF, DAF, and FAF)

in a single session.

Statistical analyses

Repeated measures analyses of variance (ANOVAs) were performed on each

of the dependent variables. Analysis for speech rate was carried out with all types of

feedback (NAF, DAF, FAF) and speech (spontaneous, reading) as within-subjects

effects, and group (CI, NH) as a between subjects effect. Analyses for percentage of

interruptions, fundamental frequency, and relative intensity, were carried out only on

reading scores due to their fixed number of syllables; therefore, analyses for these

variables were done with only the type of feedback (NAF, DAF, FAF) as within-

subjects effects, and group (CI, NH) as a between-subjects effect. Post-hoc analysis

was done using Least Significant Difference (LSD) tests. Pearson product-moment

correlations were used to measure association between dependent variables and self-

report measures of speech intelligibility among the CI users: (1) during phone

conversation, (2) when lip reading is not available, and (3) in multiple-speaker

situations.

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Results

Table 2 presents means and SDs of CI and NH participants for all dependent

variables, across feedback and speech types.

INSERT TABLE 2

Speech rate

Significant main effects were found for feedback type (F(2,36) = 13.782, p <

.001, partial η2 = .434) and speech type (F(1,18) = 13.697, p = .002, partial η2 = .432).

Speech rate was the slowest with DAF, compared to both NAF (LSD = 1.058, p <

.001) and FAF (LSD = .527, p = .001). Speech rate with FAF was also slower than

NAF (LSD = .531, p = .032). Speech rate in reading (Mean = 4.357, SD = .161) was

faster than in spontaneous speech (Mean = 3.616, SD = .181). Figure 1 presents

means and SD of speech rates in spontaneous speech (in all conditions: NAF, FAF,

DAF) for CI and NH groups. No effect was found for group on speech rate (F(1,18) =

2.221, p = .153, partial η2 = .110), nor interactions for group X feedback type (F(2,36) =

.416, p = .663, partial η2 = .023), group X speech type (F(1,18) = .427, p = .522, partial

η2 = .023), feedback type X speech type (F(2,36) = .499, p = .611, partial η2 = .027), or

group X feedback type X speech type (F(2,36) = .585, p = .562, partial η2 = .031.

INSERT FIGURE 1

Interruptions

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Figure 2 presents the mean percentage of interruptions in spontaneous speech

(in all conditions: NAF, FAF, DAF) for CI and NH groups. A significant main effect

was found for feedback type (F(2,32) = 7.683, p = .002, partial η2 = .299), but not for

group (F(1,16) = 2.209, p = .155, partial η2 = .109). A higher percentage of

interruptions occurred with DAF than NAF (LSD = .032, p = .008) or FAF (LSD =

.025, p = .022), which also had more interruptions than NAF (LSD =.007, p = .002).

No interaction of group X feedback type (F(2,32) = .656, p = .525, partial η2 = .035) was

observed.

INSERT FIGURE 2

Fundamental frequency and relative intensity

No main effects in fundamental frequency were found for group (F(1,18) =

2.277, p = .150, partial η2 = .118) and feedback type (F(2,36) = 2.165, p = .130, partial

η2 = .113), but a group X feedback type interaction was found (F(2,36) = 3.232, p =

.052, partial η2 = .160). Post-hoc repeated measures analysis showed a main effect for

feedback type only for the CI group (F(2,16) = 4.294, p = .042, partial η2 = .349), but

not for the control group (F(2,16) = 2.514, p = .127, partial η2 = .218). CI users’

fundamental frequency significantly increased following DAF, as compared to NAF

(LSD = 18.078, p = .035). No difference was observed between FAF and NAF (LSD

= 12.411, p = .103) or DAF and FAF (LSD = 5.667, p = .269).

No main effects in relative intensity were found for group (F(1,18) = .513, p =

.483, partial η2 = .029) and feedback type (F(2,36) = 1.932, p = .160, partial η2 =.102),

and no group X feedback type interaction (F(2,36) = 2.601, p = .089, partial η2 = .133)

was found.

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3.4 Self-report measures

Table 3 presents correlations for self-report intelligibility measures (phone

conversation, without lip-reading, multiple-talkers), with study dependent variables.

The ability to understand phone conversation was positively correlated with reading

aloud fundamental frequency raw score, during DAF. That is, the better CI users

understand phone conversation, the more the fundamental frequency increases while

reading aloud, during DAF. Speech intelligibility in the no lip-reading condition was

positively correlated with interruptions while reading aloud during DAF. No

significant correlations were found for the intelligibility of the multiple-talker

condition.

INSERT TABLE 3

Discussion

The current study compared the effect of altered auditory feedback on the

speech production of both adult prelingual CI users and NH individuals, in order to

evaluate the degree of reliance on auditory feedback among CI users. Both DAF and

FAF were found to affect speech production as evidenced by slower speech rates and

more interruptions while reading aloud. DAF had a larger negative effect on speech

production than FAF. The most significant study finding was the lack of difference

between CI users and NH individuals resulting from altered feedback, except for

increase in F0 during the DAF condition that appeared for CI users only. Also, of note

15

was the finding that CI users’ self-reported ability to understand phone conversation

and speech without lip-reading was positively correlated with the effects of DAF.

This finding suggests that CI users rely on auditory feedback in their daily hearing

functioning.

Significantly, this is the first study to compare CI users to NH participants on

the effects of DAF. Previous studies that tested the effect of DAF on the speech

production of hearing-impaired individuals did not compare them to the NH

population (Barac-Cikoja, 2004; Tye-Murray, 1992). Our finding that altered auditory

feedback similarly influences NH and CI users for most speech production features

(speech rate, interruptions, and relative intensity) can be considered null effect, or to

suggest that prelingual CI users have learned to rely on auditory feedback while

producing speech. This means that, like NH individuals, the speech motor system of

CI users utilizes relevant information from auditory feedback in order to fine-tune its

speech movement to achieve end goals. Our finding demonstrates a direct effect of

delayed auditory feedback on overall movement coordination in continuous speech of

CI users. Indeed, studies that previously tested CI users suggested that their reliance

on the CI increases with time (Dettman et al., 2016; Ertmer & Goffman, 2011; Tobey

et al., 2011), showing a growth in speech production abilities within the first six years

of implant use (Blamey et al., 2001; Tomblin, Peng, Spencer, & Lu, 2008). It is also

important to note that previous studies usually tested the effect of CI on prelingual

children up until their high school years and used speech intelligibility measures

(Tobey et al., 2011). Therefore, the added contribution of the present study to the

existing literature is the testing of prelingual implantees in their twenties who have

used their implants for a long period of time. Moreover, our method of using altered

feedback to assess CI users’ reliance on auditory feedback from their implants (as

16

evidenced by disrupted speech production) is a unique feature of the study design.

The results indicate that, for young adults who are prelingual CI users, reliance on

auditory feedback through their implants is already well-developed.

Although CI users, as a group, were affected by altered feedback similarly to

the NH participants in most features of speech production, we found a positive

correlation between the CI group’s daily functional hearing self-report of hearing

ability via phone, and their speech features (interruptions and F0) under DAF. This

result is in line with previous studies showing such a relationship among cochlear

implant users (Kishon-Rabin, Gehtler, Taitelbaum, Kronenberg, Muchnik, &

Hildesheimer, 2002; Tye-Murray et al., 1995). This finding is supported by the

Directions Into Velocities of Articulators (DIVA) model (Guenther, Ghosh, &

Tourville, 2006) suggests that lexical retrieval of strings of words leads to sequential

activation of speech sound map cells that send signals to cells in the auditory,

somatosensory, and primary motor cortical areas; these signals lead to production of

speech sounds through feed-forward and feedback systems. The feed-forward system

produces skilled, rapid movements that do not rely on external (auditory,

somatosensory) feedback. The feedback system teaches, refines, and updates the

movements based on error detection and correction. When auditory feedback is

removed, the production of speech relies only on the feed-forward system, along with

some somatosensory feedback. The results of the present study suggest that CI users’

feed-forward subsystem is well-tuned, similarly to that of NH individuals. The

resemblance of the experimental design to phone conversation can explain the

correlation found with this function and not the others (hearing without the

availability of lip-reading and multiple talkers’ conversation).

17

In the present study, significant changes in speech production among both

groups occurred when DAF was applied. The delay provided was 200 ms, which was

previously found to have a maximum negative effect on the speaker by making self-

monitoring of the speech signal significantly difficult for the listener (Fairbanks,

1955). Studies that previously evaluated the impact of delayed feedback on normal

hearing participants also found lower speech rates and an increase in the number of

interruptions (Kort, Nagarajan, & Houde,2014; Sasisekaran, 2012). Thus, the effect of

temporal alterations on speech production as a result of DAF was more pronounced in

the current study than the effect of spectral alterations as a result of FAF

manipulation. This finding is different from those reported in the literature showing

FAF also to have noteworthy effect on speech production, particularly in fundamental

frequency (Behroozmand et al., 2012). The discrepancy between the results of the

current and previous studies might be due to the methods of speech production

utilized in our study design. In the present study, we used continuous speech (either

reading text aloud or spontaneous speech) while most of the previous studies that

examined FAF used sustained vowels (Behroozmand et al., 2012). It may be that

when using spontaneous speech, the speaker compensates more quickly for changes

spectral pitch, relative to sustained vowels. The discrepancy also might be explained

by our study’s greater emphasis on measures of temporal changes (speech rate and

interruptions) than on spectral changes (fundamental frequency only). Thus, the

results of the current study may reflect larger sensitivity to temporal alterations.

Regarding spectral changes, the CI group showed pitch variations as a result

of DAF manipulation: Most of the CI participants showed an increase in mean

fundamental frequency under DAF during the reading aloud condition. This is in line

with the traditionally-reported finding that the pitch of hearing-impaired individuals'

18

voices are characterized as “too high” compared to normal-hearing speakers (Gilbert

& Campbell, 1980). Moreover, studies that tested short-term effects of turning off

implants also showed immediate elevation in the F0 as a result of auditory feedback

concealing (Higgins et al., 2001). Taken together with the findings of the present

study, it seems that CI users may be using this pattern of increasing their F0 when

auditory feedback is altered or nonexistent. Surprisingly, however, the NH group did

not change their F0 as a result of DAF. It may be that a delay of 200 milliseconds is

not enough to produce such a pitch change among NH participants, but for CI users,

who are more prone to increasing their F0, it is sufficient. Further studies should

explore this direction.

Declaration of Interest

The authors have no declaration of interest to report. The study was not supported by

any sponsor or funding agency.

Acknowledgment

The author would like to thank Shira Chana Bienstock for her thorough editorial

review of this manuscript.

19

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24

Table 1. Characteristics of Cochlear Implant (CI) participants

Chronological age

Mean (SD) 22.5 (4.2)

Hearing device

Two implants n=6

One implant and hearing aid n=2

One implant n=2

Age at implantation

Mean (SD) of first 4.4 (5.02)

Mean (SD) of second 13 (5.2)

Etiology of hearing loss

Genetic n=1

Cytomegalovirus (CMV) n=2

Usher syndrome n=1

Unknown n=6

Type of implant

Nucleus cochlear n=8

Advanced Bionics n=2

25

Table 2. Means and SDs for CI and NH participants on all study measures

Spontaneous Speech Reading Aloud

NH CI NH CI

Mean SD Mean SD Mean SD Mean SD

Speech rate

NAF 4.34 0.97 4.00 1.68 5.00 0.62 4.72 0.90

DAF 3.25 .99 2.77 0.95 4.29 0.86 3.52 0.97

FAF 3.68 0.80 3.65 1.06 4.59 .96 4.01 0.79

Interruptions

NAF 0% 0.00 1% 0.01

DAF 3% 0.04 5% 0.06

FAF 1% 0.01 2% 0.02

Fundamental frequency

NAF

184.74 51.21 203.97 35.81

DAF

173.39 43.17 222.04 43.47

FAF

200.66 47.16 194.16 75.81

Relative intensity

NAF

66.21 9.81 66.63 13.22

DAF

66.58 11.00 70.61 9.48

FAF

65.40 11.68 71.19 9.09

NAF = Normal Auditory Feedback; DAF = Delayed Auditory Feedback; FAF =

Frequency Altered Feedback; CI = Cochlear Implant; NH = Normal Hearing

26

Table 3. Correlations between self-report speech intelligibility measures (via phone,

without lip-reading, with multiple-talkers) and study dependent variables.

Spontaneous Speech Reading Aloud

Phone No lip-reading Multiple-talkers Phone No lip-reading Multiple-talkers

Speech rate

NAF 0.424 -0.077 0.111 0.44 0.088 0.377

DAF -0.226 -0.544 0.164 0.083 -0.176 0.268

FAF 0.42 0.097 0.373 0.559 0.308 0.451

Interruptions

NAF -0.206 -0.223 -0.574 -0.041 0.387 0.217

DAF -0.055 0.192 -0.117 0.27 .646* 0.224

FAF -0.351 -0.515 -0.662 0.229 0.43 0.152

Fundamental frequency

NAF

0.557 0.274 0.128

DAF

.786* 0.234 0.313

FAF

0.08 0.376 -0.175

Relative intensity

NAF

-0.559 -0.356 -0.274

DAF

-0.398 -0.161 -0.287

FAF

-0.473 -0.442 -0.1

NAF = Normal Auditory Feedback; DAF = Delayed Auditory Feedback; FAF =

Frequency Altered Feedback

*p<.05

27

Figure 1. Mean speech rate and SD in spontaneous speech (in all conditions: NAF,

FAF, DAF) of CI and NH groups.

28

Figure 2. Mean percentage of interruptions in spontaneous speech (in all conditions:

NAF, FAF, DAF) in CI and NH groups