Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
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Processing Speaker Variability in Repetition and Semantic/Associative Priming
Chao-Yang Lee and Yu Zhang
Ohio University
Author Note
Chao-Yang Lee, Division of Communication Sciences and Disorders, Ohio University;
Yu Zhang, Division of Communication Sciences and Disorders, Ohio University.
We thank Danny R. Moates for assistance in recruiting participants, Lauren Baer and
Eleni Gkikas for assistance in administering the experiments, and Juliana Gursky for editorial
assistance.
Correspondence concerning this article should be addressed to Chao-Yang Lee, Division
of Communication Sciences and Disorders, Ohio University, Athens, OH 45701.
E-mail: leec1@ohio.edu
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
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Abstract
The effect of speaker variability on accessing the form and meaning of spoken words was
evaluated in two short-term paired priming experiments. In the repetition priming experiment,
participants listened to repeated or unrelated prime-target pairs, in which the prime and target
were produced by the same speaker or different speakers. The results showed that the magnitude
of repetition priming was reduced when the prime and target were produced by different
speakers, indicating that speaker variability affected access to word forms. In the
semantic/associative priming experiment, participants listened to semantically/associatively
related or unrelated prime-target pairs, in which the prime and target were produced by the same
speaker or different speakers. The results showed that the magnitude of semantic/associative
priming was reduced in different-speaker trials, but only for targets produced by the female
speaker. There was no evidence that the speaker variability effect varied as a function of the
interstimulus intervals used in this study (50 ms and 250 ms). These findings suggest that
speaker variability affects spoken word recognition, but primary at a relatively shallow level of
processing.
Keywords: spoken word recognition, speaker variability, repetition priming,
semantic/associative priming
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
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Processing Speaker Variability in Repetition and Semantic/Associative Priming
Introduction
During spoken word recognition, a listener extracts information from the acoustic signals
generated by speakers and maps that information onto internal lexical representations. Lexical
representations are usually assumed to be abstract phonological codes storing only lexically
contrastive information. Therefore, the process of recognizing spoken words entails discarding
surface acoustic variability to arrive at abstract phonological codes (Johnson & Mullennix, 1997).
However, there is emerging evidence that acoustic variability is encoded in lexical
representations (e.g., Nygaard, Sommers, & Pisoni, 1994), suggesting that the mapping from
acoustic signals onto the lexicon does not necessarily involve reduction of acoustic variability
(Pisoni, 1997). Given the many sources of acoustic variability in the acoustic signals, a
foundational issue is whether all sources of acoustic variability affect spoken word recognition in
the same way. Additionally, because words/morphemes are the smallest meaningful unit of
speech, a related issue is whether acoustic variability affects access to the phonological form of
spoken words, the meaning of spoken words, or both. Given the time-sensitive nature of
processing speech, one could also ask whether various sources of acoustic variability share a
similar time course during spoken word recognition. The answers to these questions have
important implications for the nature of spoken word recognition.
The purpose of this study was to address these issues by examining the effect of speaker
variability on accessing the form and meaning of spoken words. To that end, we investigated the
effect of speaker variability on repetition priming (Forster & Davis, 1984) and
semantic/associative priming (Meyer & Schvaneveldt, 1976). Speaker variability refers to
acoustic variability generated as a consequence of the speakers’ idiosyncratic features (Luce &
McLennan, 2005). Structural features such as the shape, size and length of the vocal tract and
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behavioral features as reflected by different dialect users are potential sources of speaker
variability (Johnson & Mullennix, 1997; Palmeri, Goldinger, & Pisoni, 1993). Acoustic-phonetic
research over several decades has shown that the same spoken message can vary significantly
across speakers. However, listeners are able to understand different speakers of the same
language without much difficulty. How listeners achieve this perceptual constancy despite
speaker variability is one of the foundational issues in spoken language comprehension.
Speaker specificity in lexical representation
It is typically assumed that lexical representations are abstract and contain only lexically
contrastive information, implying that surface acoustic variability not directly relevant to lexical
identity is discarded during the signal-to-representation mapping process. By this account,
speaker-specific information would not be part of the abstract phonological code stored in lexical
representations. Consequently, memory for words should not be influenced by variability across
speakers. This prediction is supported by Jackson and Morton (1984), who used a long-term
priming paradigm to examine word recognition in a “test” phase following a “study” phase. In
the study phase, participants listened to words spoken by a female or a male speaker and made
semantic judgments about the words. In the test phase, participants listened to the same set of
words, presented in noise, which were produced by either the same speaker or different speakers.
The results showed no differences in word recognition accuracy between words spoken by the
same speaker and different speakers. Schacter and Church (1992) asked listeners in the study
phase to judge the pitch of the speakers from words spoken by six speakers. In the test phase,
listeners were asked to identify words, presented in noise, which were spoken by the same or
different speakers. Although the study phase was intended to focus the listeners’ attention on
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speaker-specific information, word recognition accuracy was similar under both the same- and
different-speaker conditions.
By contrast, other studies employing the long-term priming paradigm showed that
memory for words contains detailed information about speakers and that this information affects
word recognition. A speaker effect emerged when Schacter and Church (1992) changed their
task in the test phase (from word identification to stem completion) and presented the test stimuli
in quiet (instead of in noise). Listeners were asked to propose a multisyllabic word based on
auditory input of the first syllable of a word. This “stem completion” was more accurate when
the stimuli in the test phase were produced by the same speaker as in the study phase. Church
and Schacter (1994) asked listeners to identify words that were low-pass filtered to preserve
fundamental frequency (F0) information, but not formant information. The results showed that
word identification was more accurate when the stimuli were produced by the same speaker in
the study phase. In addition, identification accuracy was also affected by within-speaker F0
variation. Specifically, when the same speaker was used in the study and test phase, word
identification was more accurate when the F0 between study and test was the same, suggesting
that detailed F0 information is encoded in memory for words.
Subsequent studies identified additional factors that contribute to the speaker variability
effect in long-term priming. Goldinger (1996) showed that word recognition in noise was more
accurate when both study and test words were produced by the same speaker. Importantly, the
same-speaker advantage in word recognition was observed only when words were encoded at
relatively shallow levels of processing (i.e., gender and phoneme classification). By contrast, the
speaker effect was attenuated when listeners were asked to encode words at a relatively deep
level of processing (i.e., syntactic classification). There is also evidence that the speaker effect is
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contingent on response format. Luce and Lyons (1998) examined the effect of changing speaker
on auditory lexical decision (probing implicit memory) and on old/new judgment (probing
explicit memory). In the study phase, listeners made lexical decisions on word and nonword
stimuli. In the test phase, listeners either performed lexical decisions again or judged whether
each stimulus had been presented in the study phase. The results showed that responses were
faster to words that were produced by the same speaker in old/new judgment, but not in lexical
decision, indicating that speaker variability affected explicit memory, but not implicit memory.
Luce and Lyons (1998) proposed that the speaker effect did not emerge in lexical decision
because lexical decision requires rapid responses, whereas the speaker effect takes more time to
develop because speaker-specific details in lexical representations are not available as early as
the more abstract underlying forms. In other words, when processing is fast, the speaker effect is
attenuated. As processing unfolds over time, the speaker effect becomes more pronounced.
This time-course hypothesis was further tested in McLennan and Luce (2005). In three
long-term priming experiments, the authors manipulated ease of word/nonword discrimination
(easy vs. difficult) and response format (speeded vs. delayed response). These manipulations
required listeners to process words at different speeds (i.e., difficult distinctions and the delayed
response format would result in slower processing). As predicted, the speaker effect was found
only when discrimination was difficult and in the delayed response format, suggesting that
processing speaker-specific information takes time. Mattys and Liss (2008) showed that the
speaker effect on long-term priming was more pronounced in stimuli produced by dysarthric
speakers than those produced by normal control speakers. Because processing dysarthric speech
is more difficult and presumably requires more time than processing non-dysarthric speech, this
result is consistent with the idea that processing speaker-specific information requires time.
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Vitevitch and Donoso (2011) showed in a lexical decision task that it was easier for listeners to
detect a speaker change when nonword stimuli were word-like than when the stimuli were less
word-like. Because the word-like stimuli were more difficult to process, they required more
processing time than less word-like stimuli. Therefore, the better detection of speaker change in
the word-like stimuli suggests that speaker-specific information requires more time to process.
In sum, findings from these long-term priming studies indicate that speaker information
is encoded in memory for words. This observation challenges the traditional assumption that
lexical representations are highly abstract and devoid of surface acoustic variability. These
studies also suggest that processing speaker information takes time. When processing is slowed
down due to stimulus difficulty or response format, the effect of speaker variability tends to
emerge.
Speaker specificity in lexical processing
Although the long-term priming studies provided evidence for the richness of lexical
representations, it is not clear to what extent such a task can reveal the word recognition process
itself (Luce & Lyons, 1998). In particular, the process of spoken word recognition is usually
characterized by the activation of multiple word candidates and competition among the
candidates (Luce & McLennan, 2005). In addition, lexical activation and competition is a timesensitive, “on-line” process that has been extensively examined with various research paradigms
(Grosjean & Frauenfelder, 1996). Few studies, however, have examined the role of speaker
variability in these short-term lexical processes. An eye-tracking study by Creel, Aslin, and
Tanenhaus (2008) demonstrated the on-line use of speaker information in lexical disambiguation.
The stimuli included pairs of words spoken by the same speaker or different speakers. Eyetracking results showed fewer fixations on competitors for words from the different-speaker pairs
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than for words from the same-speaker pairs, indicating that speaker information facilitated
disambiguation of lexical competitors. A similar response pattern was found in a second
experiment, in which listeners learned to identify visual shapes from novel labels spoken by the
same speaker or different speakers. There were more fixations on words with same-speaker
cohorts, but fewer fixations on words with same-speaker competitors. These results indicate that
listeners are able to use speaker-specific information encoded in lexical representations during
lexical activation and competition.
Short-term paired priming is a paradigm that has been used extensively to study lexical
processing (see Zwitserlood, 1996, for a summary), but has not been applied to the study of
speaker variability. In this paradigm, a prime and a target that are related in certain ways (e.g.,
phonologically) are presented. The accuracy and latency of responses to the target are used to
evaluate the effects of the prime-target relationship, thereby revealing the organization of the
lexicon and the processes of accessing lexical representations. Of particular relevance to the
present study, short-term priming has been used to examine the effects of acoustic variability on
spoken word recognition and the time course of the effects. Andruski, Blumstein, and Burton
(1994) used short-term paired priming to investigate the effect of subphonetic variability on
lexical access. Prime-target pairs that varied in semantic/associative relationship (e.g., kingqueen) were used as stimuli, and participants were asked to make lexical decisions on the targets.
The results showed that subtle voice onset time (VOT) differences, which did not change the
perception of voicing categories, affected the magnitude of semantic/associative priming,
suggesting that detailed acoustic information was not discarded during the recognition process.
Rather, subphonetic information affected access to word meaning. In addition, the effect of
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subphonetic variability appeared at a relatively short lag (50 ms), but not at a long lag (250 ms)
between prime and target, indicating that the impact of subphonetic variability dissipated quickly.
Andruski et al. (1994) demonstrated that acoustic variability that does not alter word
identity could still affect lexical processing. The study also provided evidence for the time course
of the subphonetic variability effect. Given the multiple sources of acoustic variability in the
speech signal, one might ask whether other sources of acoustic variability, such as speaker
variability, would affect lexical processing in a similar way. Using the short-term paired priming
paradigm to investigate speaker variability could answer the following questions: Does speaker
variability affect access to word meaning as subphonetic variability does? Does speaker
variability affect access to word form in addition to word meaning? Is the magnitude and time
course of the speaker variability effect comparable to those of the subphonetic variability effect?
The answers to these questions will contribute to our understanding of the role of acoustic
variability in spoken word recognition.
The present study
In this study, the short-term paired priming paradigm was used to examine the effect of
speaker variability on accessing the form and meaning of spoken words. Repetition priming
(Experiment 1) and semantic/associative priming (Experiment 2) were used as indices of
accessing word form and meaning, respectively. In repetition priming, the processing of a word
(target) is facilitated when it is preceded by exactly the same word (prime). The magnitude of
repetition priming is usually reduced when the prime and target do not match exactly. If speakerspecific information is part of the information stored in lexical representations, the mismatch in
speaker between prime and target should result in attenuated repetition priming. In
semantic/associative priming, the processing of a target (e.g., queen) is facilitated when it is
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preceded by a semantically/associatively related prime (e.g., king). If speaker variability affects
access to word meaning, a mismatch in speaker between prime and target should result in
attenuated semantic/associative priming.
In addition, two interstimulus intervals (ISIs) were used to examine the time course of the
speaker variability effect. Andruski et al. (1994) found that subphonetic variability affected
lexical access at a short lag (50 ms), but not at a long lag (250 ms) between prime and target,
indicating the effect was short-lived. On the other hand, long-term priming studies (e.g., Luce
and McLennan, 2005) suggest that the speaker variability effect takes time to develop. The use
of both 50 ms and the 250 ms ISIs in the present study would allow for a preliminary
examination of the time course of the speaker variability effect in short-term priming. Using the
same ISIs as in Andruski et al. (1994) would also allow for a direct comparison on the time
course between the speaker variability effect and the subphonetic variability effect. The use of
these two ISIs was motivated by considerations of auditory memory and backward masking
(Andruski et al., 1994). Because auditory details are assumed to fade fast in memory, using a
short ISI ensures that a priming effect could be detected. However, too short an ISI may elicit the
effect of backward masking (the masking effect of a following stimulus leading to a failure in
perceiving the preceding stimulus). According to Massaro (1970), the effect of backward
masking from a pure tone can be perceptually neglected when the ISI is at least 250 ms. For
white noise, however, it is about 50 ms (Wilson & Carhart, 1971). Therefore, we chose 50 ms
and 250 ms as the ISIs in order to explore the time course issue.
Finally, examining both repetition and semantic priming may shed light on the issue of
depth of processing speaker variability in spoken word recognition. McLennan and Luce (2005)
noted that the depth of processing and time course of processing are usually coextensive.
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Therefore, it is difficult to discriminate between an account based on time course and one based
on depth of processing (p. 317). The present study attempted to circumvent the issue by
manipulating time course (via ISI manipulation) and depth of processing (repetition vs.
semantic/associative priming) independently. Processing semantic/associative information
presumably involves a deeper level of processing compared to processing phonological
information. Based on Goldinger’s (1996) finding that speaker-specific information affected
word recognition only when words were encoded at relatively shallow levels, it was expected
that the speaker variability effect would be more likely to emerge in repetition priming than in
semantic/associative priming. On the other hand, Andruski et al. (1994) showed that subphonetic
variability in fact affected access to word meaning, which invites the question of whether
speaker variability would have a similar effect as subphonetic variability does. Comparing the
effect of speaker variability in these two types of priming would therefore elucidate the depth of
processing issue. However, it should be noted that speaker variability is not exactly analogous to
subphonetic variability. While a change in VOT may affect word identity, variability across
speakers usually does not affect word identity. Viewed this way, speaker variability may not
affect access to word meaning as it does to word form.
In sum, the goal of the present study was to use the short-term paired priming paradigm
to explore how speaker variability affects spoken word recognition. Our major question was
whether a speaker difference between the prime and target would result in attenuated repetition
and semantic/associative priming. By using two ISIs between prime and target, this study would
allow for a preliminary examination of the time course of the speaker variability effect. By
investigating both repetition and semantic/associative priming, this study would allow for an
examination of the depth of processing issue in processing speaker variability. Compared to
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previous long-term priming studies that addressed the nature of lexical representations, the
present study is expected to extend our understanding of how speaker variability is processed
during spoken word recognition.
Experiment 1: Repetition Priming
The purpose of the repetition priming experiment was to examine the effect of speaker
variability on accessing the phonological form of spoken words. Prime-target pairs were
presented aurally to listeners, who were asked to make lexical decisions on the targets. Each
target was paired with four types of real word primes varying in word relation (repetition vs.
unrelated) and speaker relation (same speaker vs. different speakers). Table 1 illustrates the
design.
(Insert Table 1 about here)
A word relation effect (i.e., repetition priming) was expected, meaning that responses to
targets would be more accurate and/or faster when the targets were preceded by a repetition
prime. A speaker relation effect was also expected, meaning that responses to targets would be
less accurate and/or slower when the primes and targets were produced by different speakers.
The primary hypothesis to be tested in this experiment was that speaker variability would affect
the magnitude of repetition priming. We predicted that there would be a word relation  speaker
relation interaction; that is, the magnitude of the repetition priming would be reduced when the
prime and target were produced by different speakers. The time-course hypothesis (i.e., the
speaker effect takes time to develop) would also be tested. In particular, we predicted that the
word relation  speaker relation interaction would be greater at 250 ms ISI than at 50 ms ISI.
Method
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Materials. Twenty-six English words were selected as real word targets. Each target was
paired with four types of real word primes: (1) a repetition prime produced by the same speaker,
(2) a repetition prime produced by a different speaker, (3) an unrelated prime produced by the
same speaker, and (4) an unrelated prime produced by a different speaker. The targets and
unrelated primes were identical to those used in Andruski et al. (1994, p. 187). In addition, 26
pronounceable nonword items were selected as nonword targets. Each nonword target was paired
with the same set of primes as the real word targets such that listeners would not be able to
predict the lexical status of the targets. In sum, there were 104 trials with real word targets and
104 trials with nonword targets for a total of 208 trials. The complete set of stimuli is listed in the
Appendix.
A female and a male speaker of American English from the same town in central Ohio
recorded the stimuli. The recordings were made in a sound-treated booth with a condenser
microphone connected through a preamplifier and analog-to-digital converter to a computer. The
recordings were digitized with the Brown Lab Interactive Speech System (BLISS) (Mertus, 2000)
at 22050 Hz with 14-bit quantization. Each stimulus item was identified from the waveform
display and saved as an audio file. Peak amplitude was normalized across all stimulus items.
Four stimulus lists were created: (1) Targets in the prime-target pairs were produced by
the female speaker with an ISI of 50 ms. (2) Targets in the prime-target pairs were produced by
the female speaker with an ISI of 250 ms. (3) Targets in the prime-target pairs were produced by
the male speaker with an ISI of 50 ms. (4) Targets in the prime-target pairs were produced by the
male speaker with an ISI of 250 ms. Each participant was randomly assigned to receive one of
the four lists. The purpose of treating ISI and target voice as between-subject variables was to
minimize the repetition of targets during stimulus presentation. In the current design, a target is
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paired with four types of primes, meaning that the participants would hear the same target four
times during the presentation. Although assigning participants to all ISI and target voice
conditions would have had the advantage of controlling for individual variability, it would also
have resulted in even more repetitions of the targets. To minimize potential long-term repetition
effects due to the repetition, we opted to assign participants to different ISI and target voice
conditions, in addition to randomizing the order of stimulus presentation for individual
participants.
To assess the acoustic differences between the stimuli produced by the two speakers, F0
and duration of the real word targets were measured. The results are shown in Table 2. For each
word, an F0 contour was extracted by the Pitch program in BLISS with a time autocorrelation
algorithm. The extracted F0 values were then used to calculate the mean F0 for each word. As
expected, the mean F0 was higher for the female speaker than for the male speaker, t(25) = 38.4,
p < .001. Word duration was also longer for the female speaker than for the male speaker, t(25) =
6.41, p < .001.
(Insert Table 2 about here)
Participants. Sixty students (40 females and 20 males) at Ohio University participated in
the experiment. All participants were native speakers of American English. The age of the
participants ranged from 18 to 26 years (M = 20, SD = 2). All participants were screened for
normal hearing, defined as pure-tone, air-conducted thresholds of  20 dB HL at octave
frequencies from 1000 Hz to 4000 Hz.
Procedure. Participants were tested individually in a sound-treated booth. A Windows
XP personal computer equipped with the subject-testing program AVRunner in BLISS was used
for stimulus delivery and response acquisition. The participants were screened for normal
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hearing immediately before the experiment. Each participant was then randomly assigned to
receive one of the four stimulus lists. The order of stimulus presentation in a list was randomized
for each participant. The stimuli were presented through a pair of headphones connected to the
computer. The participants were told that they would be listening to pairs of word and nonword
items. Their task was to decide whether the second item in a pair was a real word or not a word
in the English language. They were told to respond with the index finger of their dominant hand
by pressing buttons labeled WORD or NONWORD on a computer keyboard. They were also
told to respond as quickly as possible because their responses would be timed. Prior to the actual
experiment, 10 practice trials were provided to familiarize the participants with the response
format. Each experimental session took approximately 20 minutes.
Data analysis. The lexical decision responses acquired by BLISS were analyzed for
accuracy and reaction time. Accuracy was defined as the percentage of correct responses to real
word targets. Nonword targets were intended as fillers and were not included in the statistical
analyses. Reaction time was measured from target onset. Only correct responses were included
in the reaction time analysis. Analyses of variance (ANOVAs) were conducted on arcsinetransformed accuracy and log-transformed reaction time with word relation (repetition vs.
unrelated) and speaker relation (same vs. different) as within-subject factors, ISI (50 ms vs. 250
ms) as a between-subject factor, and participants (F1) and stimulus items (F2) as random factors.
Because the acoustic analysis (Table 2) showed that word duration was significantly
longer for the female speaker than for the male speaker, word duration was a potential
confounding variable in the reaction time analysis. Therefore, we conducted two sets of reaction
time analysis, one based on reaction time measured from target onset and the other based on
reaction time measured from target offset. In the target-offset analysis, target duration was
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subtracted from reaction time individually for each participant and item. The two sets of analysis
generated essentially the same statistical conclusions with few exceptions. Therefore, we would
only report the results from the target-onset analysis and note the exceptions.
Results and discussion
Table 3 shows the mean accuracy of lexical decision responses. The overall accuracy was
96.5% (SD = 4.3), indicating that the participants were highly accurate in this task. An ANOVA
showed a main effect of word relation [F1(1, 58) = 41.66, p < .001, p2 = .42, F2(1, 102) = 27.13,
p < .001, p2 = .21]. The main effect of speaker relation was also significant, but only in the
analysis by participants [F1(1, 58) = 5.64, p = .021, p2 = .09]. As expected, the main effect of
word relation showed that responses to repetition trials were more accurate than those to
unrelated trials, indicating repetition priming. Contrary to intuition, the main effect of speaker
relation indicated that responses to same-speaker trials were actually less accurate than those to
different-speaker trials. However, because the difference was minimal (1%) and the overall
accuracy was quite high, the statistical difference is not likely to be of practical significance.
Therefore, the focus of our interpretation would be on the reaction time data.
(Insert Table 3 about here)
Table 4 shows the mean reaction time of lexical decision responses. An ANOVA showed
a main effect of word relation [F1(1, 58) = 253.02, p < .001, p2 = .81, F2(1, 102) = 642.07, p
< .001, p2 = .86]. The word relation  speaker relation interaction [F1(1, 58) = 7.4, p = .009, p2
= .11, F2(1, 102) = 5.95, p = .016, p2 = .06] was also significant. The analysis by items further
revealed a main effect of ISI [F2(1, 102) = 4.14, p = .044, p2 = .04]. There were no other effects.
As expected, the main effect of word relation showed that responses to the repetition trials were
faster than those to the unrelated trials, indicating repetition priming. Importantly, the word
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relation  speaker relation interaction indicated that the magnitude of repetition priming differed
between the same- and different-speaker trials. As predicted, the degree of facilitation by
repetition primes was reduced when the prime and target were produced by different speakers.
As for the effect of ISI, although the reduction of priming due to different speakers appeared to
be more pronounced at 250 ISI as was predicted, the word relation  speaker relation  ISI
interaction did not reach statistical significance [F1(1, 58) = 3.19, p = .079; F2(1, 102) = 0.85, p
= .358]. Finally, the word relation  speaker relation interaction did not reach statistical
significance in the analysis of reaction time measured from target offset.
(Insert Table 4 about here)
In sum, the accuracy analysis showed that participants were highly accurate in this task,
justifying the use of reaction time as a relevant dependent measure. As expected, both accuracy
and reaction time analyses showed robust repetition priming. Contrary to expectation, however,
processing same-speaker trials was neither more accurate nor faster than processing differentspeaker trials. The absence of same-speaker advantage could be due to the repetition of targets
and the use of only two speakers. These two factors could have resulted in excessive familiarity
with the speakers, neutralizing the speaker relation effect.
Nonetheless, the primary prediction of the experiment (i.e., repetition would be
attenuated when prime and target were produced by different speakers) was supported by the
reaction time result. The magnitude of repetition priming was reduced when different speakers
produced the prime and target than when the same speaker produced the prime and target. This is
to our knowledge the first demonstration of short-term repetition priming being modulated by
speaker variability.
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By contrast, the prediction about the time course of speaker variability in repetition
priming was not supported by the data. It was predicted that the reduction of repetition priming
due to speaker variability would be more pronounced at 250 ms ISI than at 50 ms ISI. Although
the trend observed in the data is consistent with the prediction, the difference was not statistically
significant. Based on the trend, it is speculated that an effect might emerge at a longer ISI than
those examined in this experiment.
Experiment 2: Semantic/Associative Priming
Results from the repetition priming experiment showed that speaker variability affected
access to word form. The magnitude of repetition priming was attenuated when the prime and
target were produced by different speakers. The purpose of the present experiment was to
examine whether speaker variability would have a similar effect on accessing word meaning. As
in the repetition priming experiment, prime-target pairs were presented aurally to listeners, who
were asked to make lexical decisions on the targets. The targets used in this experiment were
identical to those used in the repetition priming experiment. Each target was paired with four
types of real word primes varying in word relation (semantic/associative vs. unrelated) and
speaker relation (same speaker vs. different speakers). Table 5 illustrates the design. As in the
repetition priming experiment, two ISIs (50 ms and 250 ms) were used to explore the time course
of the speaker variability effect. Because semantic/associative relationship presumably involves
a deeper level of processing than processing word form, results from the present experiment
could be compared to those from the repetition priming experiment to address the depth of
processing issue regarding speaker variability.
(Insert Table 5 about here)
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A word relation effect (i.e., semantic/associative priming) was expected, meaning that
responses to targets would be more accurate and/or faster when the targets were preceded by a
semantically/associatively related prime. A speaker relation effect was also expected, meaning
that responses to targets would be less accurate and/or slower when the primes and targets were
produced by different speakers. However, the absence of the speaker relation effect on repetition
priming suggests that this effect might not be obtained in semantic/associative priming. That is,
if speaker variability does not affect access to word forms, it is unlikely to affect access to word
meaning. The primary hypothesis to be tested in this experiment was that speaker variability
would affect the magnitude of semantic/associative priming. We predicted that there would be a
word relation  speaker relation interaction; that is, the magnitude of semantic/associative
priming would be reduced when the prime and target were produced by different speakers. If so,
the result would indicate that speaker variability affects not only access to word form, but also
access to word meaning. Finally, the time-course hypothesis would be evaluated. If processing
speaker variability effect takes time, the word relation  speaker relation interaction should be
greater at the longer ISI (250 ms). Alternatively, if the time course of processing speaker
variability is similar to that of subphonetic variability (Andruski et al., 1994), the word relation 
speaker relation interaction should be greater at the shorter ISI (50 ms).
Method
Materials. The targets used in this experiment were identical to those used in the
repetition priming experiment. Each target was paired with four types of real word primes: (1) a
semantically/associatively related prime produced by the same speaker, (2) a
semantically/associatively related prime produced by a different speaker, (3) an unrelated prime
produced by the same speaker, and (4) an unrelated prime produced by a different speaker. Both
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
20
the primes and targets were identical to those used in Andruski et al. (1994). The same 26
pronounceable nonword items as in the repetition priming experiment were selected as nonword
targets. Each nonword target was paired with the same set of primes as the real word targets. In
sum, there were 104 trials with real word targets and 104 trials with nonword targets for a total
of 208 trials. The stimuli are listed in the Appendix. The same female and male speakers as in the
repetition priming experiment recorded the stimuli. Four stimulus lists were created varying in
target voice (female vs. male) and ISI (50 ms vs. 250 ms). Each participant was randomly
assigned to receive one of the four lists.
Participants. Sixty students (45 females and 15 males) at Ohio University participated in
this experiment. All participants were native speakers of American English. The age of the
participants ranged from 18 to 25 years (M = 20, SD = 2). All participants were screened for
normal hearing as defined earlier in the repetition priming experiment. None of the participants
participated in the repetition priming experiment.
Procedure. The procedure was identical to that used in the repetition priming experiment.
Data analysis. The same data analyses were performed as in the repetition priming
experiment, except that the two levels of word relation were now semantically/associatively
related and unrelated. In addition, we included an extra factor of target voice (female vs. male) in
the statistical analyses. Although no predictions were made regarding target voice, preliminary
data analysis showed distinct patterns between responses to the two speakers. Therefore, we
decided to report data by target voice as well. In other words, there were two within-subject
factors (word and speaker relation) and two between-subject factors (ISI and target voice) in the
current experiment.
Results and discussion
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
21
Table 6 shows the mean accuracy of lexical decision responses. The overall accuracy was
96.4% (SD = 3.5), indicating that the participants were highly accurate in this task. An ANOVA
showed a main effect of word relation [F1(1, 56) = 21.02, p < .001, p2 = .27, F2(1, 100) = 15.73,
p < .001, p2 = .14]. As expected, responses to semantically/associatively related trials were more
accurate than those to unrelated trials, indicating semantic/associative priming. There were no
other effects. As in the repetition priming experiment, the overall accuracy of lexical decision
responses was fairly high. Therefore, our interpretation would focus on the reaction time results.
(Insert Table 6 about here)
Table 7 shows the mean reaction time of lexical decision responses. An ANOVA showed
a main effect of word relation [F1(1, 56) = 225.82, p < .001, p2 = .80, F2(1, 100) = 128.98, p
< .001, p2 = .56] and a main effect of target voice [F1(1, 56) = 6.95, p = .011, p2 = .11, F2(1,
100) = 11.17, p = .001, p2 = .10]. There were also two interactions: speaker relation  target
voice [F1(1, 56) = 11.02, p = .002, p2 = .16, F2(1, 100) = 6.18, p = .015, p2 = .06] and word
relation  speaker relation  target voice [F1(1, 56) = 5.80, p = .019, p2 = .09]. As expected, the
main effect of word relation showed that responses to semantically/associatively related trials
were faster than those to unrelated trials, indicating semantic/associative priming. The main
effect of target voice showed that responses to the stimuli produced by the male speaker were
faster. However, recall that the acoustic analysis showed that the average duration of stimuli
produced by the male speaker was shorter (Table 2), suggesting that the faster response to the
male speaker could be due to the shorter stimulus duration. Indeed, the analysis on reaction time
measured from target offset did not show an effect of target voice.
As for the primary hypothesis that the magnitude of priming would be attenuated when
the prime and target were produced by different speakers, we did not find a significant word
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
22
relation  speaker relation interaction as was found in the repetition priming experiment.
However, the highest order interaction (word relation  speaker relation  target voice) indicated
that the magnitude of semantic/associative priming depended on both speaker relation and target
voice. In particular, Table 7 shows that the magnitude of semantic/associative priming was
reduced in different-speaker trials, but only when the target was produced by the female speaker.
By contrast, when the target was produced by the male speaker, the magnitude of
semantic/associative priming was not attenuated in the different-speaker trials.
(Insert Table 7 about here)
In sum, the accuracy analysis again showed that participants were highly accurate in this
task. As expected, both accuracy and reaction time analyses showed robust semantic/associative
priming. As in the repetition priming experiment, there was no overall effect of speaker relation.
Responses to same- and different-speaker trials were comparable in both accuracy and reaction
time. Although this result was somewhat counterintuitive, it could be anticipated from a similar
null result in the repetition priming experiment. That is, if speaker variability does not affect
access to word form, it is unlikely to affect access to word meaning.
The critical result from this experiment was the word relation  speaker relation  target
voice interaction. Unlike repetition priming, semantic priming was modulated not only by
speaker relation but also by target voice. The magnitude of semantic/associative priming was
attenuated in the different-speaker trials, but only when the target was produced by the female
speaker. An alternative way of describing this result is that there was more priming when the
female speaker produced the prime than when the male speaker produced the prime. Since the
female speaker took longer to produce the primes, listeners might have had more time to process
the primes by the time the target arrived, resulting in the more pronounced priming. Compared to
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
23
repetition priming, the absence of a robust word relation  speaker relation interaction suggests
that as the level of processing becomes deeper (from form to meaning), the impact of speaker
variability becomes less prominent. In other words, acoustic details arising from speaker
differences may not be as important in accessing word form as in accessing word meaning.
Finally, there was no evidence that the reduction in semantic/associative priming varied between
the two ISIs. This null result did not allow us to distinguish between the time-course hypothesis
(Luce & Lyons, 1998) and the transient nature of processing acoustic variability (Andruski et al.,
1994). As noted in the discussion of Experiment 1, using a longer ISI may allow for a further test
of the time course of processing speaker variability in priming.
General Discussion
The research question addressed in this study was whether speaker variability affects
spoken word recognition. Specifically, we asked whether speaker variability would affect the
magnitude of short-term priming, whether the effect would be found at the level of accessing the
form or meaning of spoken words, and what would be the time course of the speaker variability
effect. In addition to the well-documented repetition and semantic/associative priming effects,
the primary prediction of the study was that the magnitude of priming would be reduced when
the prime and target were produced by different speakers. We also predicted that the reduction
would be more prominent in repetition priming than semantic/associative priming. In addition,
based on the time-course hypothesis (Luce & Lyons, 1998), we expected that the reduction in
repetition priming would be more pronounced at the longer ISI (250 ms). Based on Andruski et
al. (1994), we expected that the reduction in semantic/associative priming would be more
pronounced at the shorter ISI (50 ms).
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24
Because the accuracy of lexical decision responses in both experiments were near ceiling,
our interpretations focused on the reaction time results. As expected, the results showed robust
repetition priming (Forster & Davis, 1984) and semantic/associative priming (Meyer &
Schvaneveldt, 1976). The average facilitation by a repetitive prime was 169 ms, and the average
facilitation by a semantic/associative prime was 73 ms. The magnitude of semantic/associative
priming was somewhat smaller than what was found in Andruski et al. (1994), who showed
semantic/associative priming of approximately 100 to 150 ms with the same set of stimuli as in
the present study (p. 174 & 178).
Importantly, the magnitude of facilitation in both repetition and semantic/associative
priming varied as a function of speaker relation, indicating that priming was dependent on
speaker-specific information. As noted in the introduction, long-term priming studies showed
that word recognition/memory was slower and/or less accurate by using different speakers across
the study and test phases (Schacter & Church, 1992; Church & Schacter, 1994; Goldinger, 1996;
Luce & Lyons, 1998; McLennan & Luce, 2005; Mattys & Liss, 2008; Vitevitch & Donoso,
2011). The reduction in the magnitude of priming is usually interpreted as the prime having
activated a different lexical form (Luce & Lyons, 1998), suggesting that lexical representation
contains speaker-specific information. In the present study, the reduction in the magnitude of
short-term repetition priming in different-speaker trials could similarly suggest that the same
word produced by different speakers was processed as different lexical forms. That is, because
the prime did not activate the same lexical form, in which speaker information was encoded,
there was not as much facilitation as there was when the prime and target were produced by the
same speaker.
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25
Alternatively, the reduction in repetition priming could be due to short-lived processes,
but not due to activation of a different lexical form. Compared to the long-term repetition
priming studies, listeners in the present study had much less time to actually encode the primes
before they had to process and respond to the targets. Therefore, the reduction in repetition
priming could reflect listeners’ making online perceptual adjustments to speaker differences, a
process commonly referred to as speaker normalization (Pisoni, 1997). Although the present
results cannot distinguish these two interpretations, available evidence on the representation (e.g.,
the long-term repetition priming studies reviewed earlier) and on-line processing (e.g., Creel et
al., 2008, and the present study) of spoken words clearly suggests that lexical forms contain
speaker-specific information and that this information is used during the online recognition
process.
The effect of speaker variability, however, was less evident in the processing of word
meaning. In the semantic/associative priming experiment, the magnitude of priming was reduced
when the prime and target were produced by different speakers. However, this conclusion holds
only when the targets were produced by the female speaker, but not the male speaker. A few
observations could be made from this result. First, when both target voices were considered
together, the reduction of semantic/associative priming in the different-speaker trials was not
statistically significant, indicating that the effect of speaker variability on accessing word
meaning was not conclusive. In the repetition priming experiment, the average magnitude of
facilitation in the same-speaker trials was 26 ms. By contrast, this facilitation disappeared in the
semantic/associative priming experiment. The same-speaker trials in fact resulted in an average
of 2 ms of inhibition, largely due to the results from the male speaker. Because word meaning
presumably involves a deeper level of processing than word form, these results suggest that the
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
26
speaker variability effect occurs primarily at a relatively shallow level of processing (Goldinger,
1996). The lack or inconsistency of facilitation in semantic/associative priming suggests that the
effect of speaker-specific information does not persist to accessing word meaning.
Second, the absence of reduction by speaker variability in semantic/associative priming
contrasts with Andruski et al. (1994), who found that subphonetic variability affected access to
word meaning. Andruski et al. (1994) showed that fine acoustic structure (i.e., VOT) that did not
change phonetic category (i.e., voicing) could still impact access to word meaning. Although
both subphonetic and speaker variability involve changes in fine acoustic structure, this contrast
suggests that they are processed differently during spoken word recognition. Alternatively, as
noted in the introduction, this contrast could be due to the nature of the two sources of acoustic
variability. A change in VOT is more likely to affect word identity than a change of speakers is.
Therefore, it may not be too surprising that speaker variability did not affect access to word
meaning as much as subphonetic variability does.
This conclusion, however, is tentative because a reduction in semantic/associative
priming was in fact observed when the targets were produced by the female speaker. That is, the
reduction of priming due to speaker variability depended on the specific voice used for the
targets. Dialect difference is unlikely to account for the contrast between the two target voices
because both speakers grew up in the same town. Intelligibility difference is also unlikely to be
the reason because there was no overall effect of target voice in response accuracy. On the other
hand, because the two speakers were of different genders, the speaker effects could be a gender
effect, but not a speaker effect per se. As a first attempt to employ the short-term paired priming
paradigm to investigate the speaker variability effect, our motivation for using speakers of
different genders was to maximize the speaker differences such that a speaker effect could be
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27
detected. Future studies could use speakers of the same gender to control for the contribution of
speaker gender. A second possibility for the contrast between the female and male results is that
the listeners might have had more time to process the female stimuli, which allowed the speaker
effect to surface. As shown in the acoustic analysis, average duration of the female stimuli was
longer than that of the male stimuli. Results from the reaction time analysis also showed that
responses to female stimuli were slower. It is possible that listeners had more time to process the
female stimuli, which allowed speaker-specific information to affect semantic/associative
priming.
The potential relevance of time, however, was not supported by the ISI analyses. Based
on the time-course hypothesis (Luce & Lyons, 1998), it was expected that reduction of repetition
priming due to speaker variability would be more pronounced at the longer ISI (250 ms). Based
on Andruski et al.’s (1994) finding regarding subphonetic variability, it was expected that
reduction of semantic/associative priming due to acoustic variability would be more pronounced
at the shorter ISI (50 ms). Neither prediction was supported by the data, i.e., the word relation 
speaker relation  ISI interaction was not statistically significant. Therefore, no conclusion could
be drawn from the current study regarding the time course of the speaker variability effect in
short-term priming. However, we did observe a trend of more pronounced reduction of repetition
priming due to speaker variability at the longer ISI (250 ms), which would be consistent with the
time-course hypothesis. We suspect that the ISIs used in the present study were not within the
time frame in which speaker variability would exert its effect on spoken word recognition.
Future studies could investigate whether a longer ISI will allow the speaker variability effect to
emerge.
Conclusion
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28
The present study contributes to the literature on spoken word recognition by examining
the processing of speaker variability in two well-established cognitive phenomena, i.e., shortterm repetition and semantic/associative priming. Complementing long-term priming studies that
showed the relevance of speaker information in lexical representations, the present study is the
first to demonstrate that speaker variability affects the access to word form, as indicated by a
reduction in the magnitude of short-term repetition priming. By investigating both repetition and
semantic/associative priming, the present study was able to address the depth of processing for
speaker variability. With the use of two ISIs, the present study allowed for a preliminary
investigation of the time course of the speaker variability effect. With the same set of stimuli as
used in Andruski et al. (1994), the present study allowed for a direct comparison between two
common sources of acoustic variability. Our findings indicated that speaker variability affects
access to word form to a greater extent than it does access to word meaning, suggesting that
speaker variability was processed at a relatively shallow level. The time course of processing
speaker variability, however, is not conclusive from the current data. Given that only two
speakers were used for the stimuli and that gender was a potential confound, future studies could
explore the role of speaker variability in priming by using more speakers, controlling for speaker
gender, and using ISIs that are longer than those employed in the current study.
Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
29
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Running head: PROCESSING SPEAKER VARIABILITY IN PRIMING
Table 1
An example of the repetition priming experimental setup
Prime (speaker) Target (speaker)
queen (male)
queen (male)
queen (female)
bell (male)
bell (female)
Word relation
repetition
repetition
unrelated
unrelated
Speaker relation
same
different
same
different
32
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33
Table 2
Mean F0 (in Hz) and duration (in ms) of word targets produced by the speakers
Mean F0
Word
queen
dog
pie
shawl
stick
spy
bread
bottom
exam
pin
short
foot
wild
coach
book
war
forest
step
friend
verse
drug
hand
fruit
mine
hurt
hug
M (SD)
Male
117
105
112
114
116
105
106
107
112
112
144
123
100
119
114
118
105
117
107
112
112
108
117
105
114
110
113 (8)
Duration
Female
225
213
220
212
236
209
199
190
200
216
245
240
207
227
243
202
214
237
204
210
197
197
247
199
242
205
217 (18)
Male
455
476
383
573
632
688
388
353
584
430
643
436
673
551
345
471
589
635
529
479
486
589
467
475
391
413
505 (102)
Female
543
544
559
678
726
775
511
538
802
395
798
580
505
671
450
474
728
785
745
569
599
616
749
685
625
504
621 (118)
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34
Table 3
Mean accuracy of lexical decision responses (in % with SD, n = 15) in the repetition priming
experiment
ISI (ms)
50
250
M
Same speaker
Repetition
Unrelated
97 (3)
95 (7)
98 (4)
95 (4)
98 (3)
95 (6)
M
96 (6)
96 (4)
96 (5)
Different speakers
Repetition
Unrelated
98 (3)
96 (5)
98 (3)
96 (4)
98 (3)
96 (4)
M
97 (4)
97 (3)
97 (4)
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35
Table 4
Mean reaction time of lexical decision responses (in ms with SD, n = 15) and magnitude of
facilitation in the repetition priming experiment
ISI (ms)
50
250
M
Same speaker
Repetition
Unrelated
747 (114)
921 (126)
784 (149)
974 (154)
765 (133)
947 (142)
Facilitation
174
190
182
Different speakers
Repetition
Unrelated
764 (122)
929 (110)
802 (139)
948 (124)
783 (131)
939 (116)
Facilitation
166
146
156
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Table 5
An example of the semantic/associative priming experimental setup
Prime (speaker) Target (speaker)
king (male)
queen (male)
king (female)
bell (male)
bell (female)
Word relation
semantic/associative
semantic/associative
unrelated
unrelated
Speaker relation
same
different
same
different
36
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37
Table 6
Mean accuracy of lexical decision responses (in % with SD, n = 15) in the semantic/associative
priming experiment
ISI (ms)
50
250
Target voice
Female
Male
M
Female
Male
M
Same speaker
Semantic Unrelated
96 (4)
95 (5)
98 (3)
95 (3)
97 (4)
95 (4)
99 (2)
94 (5)
98 (2)
95 (3)
98 (2)
95 (4)
M
96 (4)
96 (3)
96 (4)
96 (4)
97 (3)
97 (4)
Different speakers
Semantic Unrelated
97 (4)
96 (4)
98 (2)
96 (4)
97 (3)
96 (4)
97 (3)
96 (4)
97 (3)
95 (3)
97 (3)
96 (3)
M
97 (4)
97 (3)
97 (4)
97 (3)
96 (3)
96 (3)
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38
Table 7
Mean reaction time of lexical decision responses (in ms with SD, n = 15) and magnitude of
facilitation in the semantic/associative priming experiment
ISI
(ms)
50
250
Target
voice
Female
Male
M
Female
Male
M
Same speaker
Semantic Unrelated Facilitation
Different speakers
Semantic Unrelated Facilitation
857 (90)
775 (104)
816 (104)
892 (144)
823 (171)
858 (159)
848 (113)
774 (106)
811 (114)
881 (141)
816 (156)
848 (150)
942 (110)
834 (115)
888 (124)
989 (139)
869 (135)
929 (148)
85
59
72
97
46
71
915 (101)
856 (88)
886 (98)
945 (132)
899 (156)
922 (144)
67
82
75
64
83
74
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39
Appendix. List of stimuli used in the experiments
Semantically/associatively
related primes
king
cat
cake
cape
cane
code
toast
top
test
tack
tall
toe
tame
team
page
peace
pine
pace
pal
poem
pill
palm
pear
pit
pain
pet
Unrelated
primes
bell
fort
seed
meat
sheet
joke
size
nut
rag
thief
choice
hill
fan
rain
week
hip
seal
gift
yawn
fog
race
job
jet
sound
niece
mesh
Repetition
primes/Word targets
queen
dog
pie
shawl
stick
spy
bread
bottom
exam
pin
short
foot
wild
coach
book
war
forest
step
friend
verse
drug
hand
fruit
mine
hurt
hug
Nonword targets
/ɡlɔ/
/θrɪdʒ/
/ɡaɪnd/
/dɛnd/
/ɡraɪs/
/fʌlə˞/
/dost/
/ʌŋk/
/tʃɑrʃ/
/mʊk/
/tɪtʃ/
/ɡɑrt/
/dʒɑʊn/
/lɜ˞d/
/ɡʊʃ/
/ʃɔɪl/
/wɛɡ/
/dʒæft/
/klænt/
/tʃænd/
/kruθ/
/hjul/
/wɪndʒ/
/ʃaʊs/
/ve/
/tɛlt/