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The relationship between diadochokinetic rate and accuracy,
reading, rate, and sentence intelligibility in Cantonese speakers
with Parkinsonism
University of Hong Kong
Tsang, Suk-ling, Esther; 曾淑玲
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2001
http://hdl.handle.net/10722/56247
This work is licensed under a Creative Commons AttributionNonCommercial-NoDerivatives 4.0 International License.; The
author retains all proprietary rights, such as patent rights and
the right to use in future works.
The relationship between diadochokinetic rate and accuracy, reading rate, and
sentence intelligibility in Cantonese speakers with Parkinsonism
Tsang Suk Ling Esther
A dissertation submitted in partial fulfillment of the requirements for the Bachelor of
Science (Speech and Hearing Sciences), The University of Hong Kong, May 4,2001.
Abstract
This study examined the relationship between nonspeech tasks (DDK rate and
DDK accuracy) and speech tasks (reading rate and sentence intelligibility) in speakers
with Parkinson's disease (PD). Eleven speakers with PD, aged between 43 and 78,
served as speaker subjects. DDK rate and DDK accuracy were analyzed using
perceptual and acoustical analysis. Reading rate was analyzed by calculating
syllables per second. For the sentence intelligibility, six naive listeners
orthographically transcribed sentences.
The results showed a moderate correlation between DDK accuracy (as measured
perceptually) and sentence intelligibility, and a moderate correlation between
perceptual and acoustic measures of DDK accuracy All other coixelations between
DDK rate, reading rate, sentence intelligibility and DDK accuracy (perceptual and
acoustic) were nonsignificant. It appeared that the nonspeech tasks (DDK rate and
DDK accuracy [as measured acoustically]) were not a very good predictor of speech
tasks, at least for sentence intelligibility and reading rate. Possible explanations of
thefindingsare discussed.
i
Introduction
Parkinson's disease (PD) is a neurologic syndrome caused by changes in certain
parts of the extrapyramidal system. The most obvious change is depigmentation of
the substantia nigra, with a loss of dopamine (Darley, Aronson, & Brown, 1975).
The major feature involved in extrapyramidal disease is hypokinesia, or limitations in
movement. A decrease in the range, rate, and mobility of movements; the presence
of rigidity and rest tremor; and a loss of automatic movement are characteristics of
hypokinesia (Darley, et al., 1975). These abnormal movements in neuromuscular
structures lead to the speech disorders found in these patients. The speech disorders
associated with PD have been well-documented. Darley et al. described "monopitch,
monoloudness, reduced stress, imprecise consonants and variable rate, etc." (1975,
p. 193). Imprecise consonants and variable rate are the focuses of the current study.
Canter (1965) and Darley, et al (1975) reported plosive consonants lacked precision,
and a discoordination of articulatoiy activity in speakers with PD. Variable
diadochokinetic (DDK) rate in speakers with PD was reported by Ackermann,
Hertrich & Hehr (1995). Also, Canter (1963) found speakers with PD had variable
reading rate.
A variety of speech and nonspeech tasks are used in assessing motor speech
disorders of neurological patients, including patients with PD. The role of
nonspeech tasks in assessment is controversial. Nonspeech assessments sometimes
are used to differentiate different neurological patientsfromnormals (Robin, Solomon,
Moon, & Folkins, 1997). Also, nonspeech tasks have the advantage of investigating
the performance of individual sensorimotor subsystems and the intactness of certain
structures that produce speech without the complication of any linguistic demand
(Robin et al., 1997). However, some researchers have doubted whether nonspeech
i
tasks can reflect natural speech production. Kreul (1972) claimed that motor control
for speech may not be predicted by nonspeech movements. Also, Weismer & Liss
(1991) stated that we cannot assume a relationship between performance in motoric
subsystem (as measured by nonspeech task) and overall speech performance.
However, Canter (1965) suggested that better neuromuscular performance in
nonspeech tasks (e.g. rate of articulators) corresponds to better speech production.
Also, Folkins, Moon, Luschei & Robin (1995), suggested that motoric nonspeech
tasks may relate to natural speech. Therefore, the predictive value of nonspeech
tasks to natural speech assessment is still unresolved (Robin, et al., 1997). Further
investigation of the relationships between nonspeech and speech tasks is needed.
In the present study, the nonspeech and speech tasks selected to investigate were
related to the speech disorders seem in speakers with PD. As mentioned earlier,
imprecise consonants and variable rates are two of the most salient speech features of
Parkinson's disease (Darley et al, 1975). This study was intended to investigate the
relationship between nonspeech tasks (including DDK) and speech tasks (including
reading rate and sentence intelligibility), DDK tasks are considered a speech task by
some people (e.g. Duffy, 1995) but a nonspeech task by the others (e.g. Robin et al,
1997). In the present study, we will follow the definition of Robin et al. (1997), in
defining DDK as a nonspeech task, because DDK does not involve any linguistic
content Also, it is believed that in the production of DDK trains, only one structure
(e.g. labial) or maximally, the coordination of three structures (labial, tongue tip and
tongue blade) are involved. Coordination is thus greatly simplified and is specified
to certain movements.
Diadochokinesis is defined as 'the maximum speed of movement with which a
given reciprocating act can be produced" (Lundeen, 1950, p.54). DDK analysis may
3
include the measurement of rate and accuracy of placement (Forrest & Weismer, 1997)
which will be discussed separately. DDK rate is considered a maximum
performance test (MPT). It can reflect diminished coordination, range or rate of
articulators in clinical neurology (Kent, Kent & Rosenbek, 1987). In the present
study, both monosyllabic and trisyllabic DDK sequences were studied because both
are widely used in clinical assessment of motor speech disorder, as supplements to the
perceptualfindings(Wit, Maassen, Gabreels & Thoonen, 1993; Tjaden, 2000).
Apartfromthe advantages of nonspeech task stated above, there are other advantages
of using nonspeech tasks, specifically DDK rate. Andrews, Piatt, and Young (1977)
reported DDK rate could predict articulatory performance. It might be because
DDK rate is sensitive to oromotor deficits (Ackermann, Hertrich & Hehr, 1995). It
is also a quantitative measurement which is objective and easy to be carried out. In
the present study, DDK rate was analyzed both instrumentally and perceptually.
DDK accuracy is defined as accuracy of articulation in DDK trains. In the
present study, DDK accuracy involved two parameters: 1/ Target accuracy (TA), using
perceptual analysis. 2/ Complete occlusion (CO), using acoustic analysis. There
are some advantages of using DDK accuracy, it measures undershooting of
articulatory gestures, hence reflects the range of movement of articulators. DDK
accuracy also provides invaluable information of dysarthric speech by differentiating
neurological groupsfromnormal. Speakers with PD were reported to have
significantly lower DDK accuracy than the normal (Ackermann, Hertrich, & Hehr,
1995; Ackermann, Grone, Hoch & Schonle, 1993).
Speaking rate is "a measure of the amount of speech produced per unit time, it is
frequently expressed in syllables per second" (Tijaden, 2000, p.997). Reading rate is
similar to speaking rate but structured laboratory reading materials are used.
4
Reading rate and speaking rate have been studied in dysarthria (Kreul, 1972; Turner
& Weismer, 1993). Although reading rate could not be considered the same as
natural spontaneous speech (Canter, 1963), reading rate is more easy to control and
measure as structured speech materials are used. It provides uniforai speech samples
which allow comparsions between individual speakers and groups more easily and
reliably (Canter, 1963; Tijaden, 2000).
Intelligibility means "the understandability of speech" (Yorkston, Dowden and
Beukelman, 1992, p.265). Speech intelligibility in words, sentences, and connected
discourse has been widely used in evaluating dysarthric speech (Yorkston et al., 1992).
Sentence intelligibility was the focus of this study as it is easier to measure than
connected discourse but approximates natural speech more closely than single word
production (Ackermann & Ziegler, 1991). In this study, the method of direct
transcription was employed to evaluate intelligibility, rather than scaling procedures.
Although direct transcription is time-consuming, it is considered more reliable and
valid (Schiavetti, 1992).
Investigation of the relationships between DDK rate, reading rate, DDK accuracy,
and speech intelligibility have been carried out in several previous studies (Canter,
1965; Ackermann, & Ziegler, 1991). However, the results were inconsistent. As
we know, DDK rate is widely used in clinical assessment (Darley et al, 1975), as it
may predict articulatory competence. Correlations were obtained between DDK rate
and speech intelligibility in several studies (Canter, 1965; Dworkin & Aronson, 1986;
Buck & Cooper, 1956). In Canter (1965), a strong correlation (0.87) between DDK
rate and "clarity of articulation'* (p.221) was obtamed. Moderate correlations
between DDK rate and speech intelligibility (0.45-0.59) were reported by Dworkin &
Aronson (1986). But in Buck & Cooper (1956), there was no significant correlation
5
between DDK rate and speech adequacy. Differences in the research methods across
studies may account for the different results. First, speech intelligibility was defined
differently.
Buck & Cooper (1956) measured speech adequacy, which may involve
many speech parameters, include prosody whereas Canter (1965) and Dworkin &
Aronson (1986) measured clarity of articulation. Second, in Dworkin & Aronson
(1956), dysarthric speakers with different neurological origins were investigated
whereas in Canter (1965) and Buck & Cooper (1956), only Parkinson's patients were
involved. As Luschei (1991) stated, it is not certain how DDK is related to speech
task. The contradictory evidence arouses interest to further investigate the
relationship between DDK rate and intelligibility.
Inconsistent correlations between reading rate and DDK rate have also been
found (Kreul, 1972; Tiffany, 1980). In Kreul (1972), there was a mild-to-moderate
correlation between reading rate and DDK rate while in Tiffany (1980), no significant
correlation was obtained between simple repetition rate (including DDK rate) and
reading rate. It would seem that DDK rate and reading rates should correlate with
each other as they appear measure the same parameter. However, reading rates
involves complex factors, such as phonetics and linguistics while DDK rate, which is
a kind of repetition rate, is a highly artificial test of simple motor movements (Tiffany,
1980). Given the inconsistency of previous results and the lack of recent
investigations of speakers with PD. It seems valuable to further investigate the
relationship between DDK rate and reading rate.
In addition to DDK rate, DDK accuracy was a concern of the present study.
Speakers with PD always undershoot articulator^ target or produce sustained /a/
instead of the target CV syllables than normals, it might be caused by fast DDK rates
(Ackermann, Hertrich & Hehr, 1995; Ackermann, Grone, Hoch & Schonle, 1993),
6
Therefore, articulatory accuracy in DDK sequences may also be a valuable tool in
assessment, especially in its possible relationship to DDK rate and sentence
intelligibility. Ackermann, Hertrich & Hehr (1995) reported a tendency for speakers
with PD to have normal DDK rate, but to undershot the articulatory target, while
speakers with Friedreich's ataxia had slower DDK rate, but achieved the articulatory
target more. This would suggest a relationship between DDK rate and DDK
accuracy. However, a statistical of such a correlation has not been reported. On the
other hand, a significant correlation (r=0.64) has been found between articulatory
accuracy (CO) and severity of overall articulatory impairment (Ackermann & Ziegler,
1991). However, the analysis of undershooting of articulators was done in sentences,
but not DDK trains. The present study was intended to extend the above studies.
In addition to, perceptual judgment of DDK accuracy (TA) was added, which may be
more accessible in clinical practice.
Until now the relationships between all four of these factors (DDK rate, DDK
accuracy, reading rate, sentence intelligibility) have not been explored. Determining
the relationship between these four factors may be helpful in evaluating the value of
simple nonspeech tasks (DDK rate and DDK accuracy) in the assessment of motor
speech disorders. Nonspeech tasks are time-efficient and widely used by speech
pathologists. However, their efficacy in predicting severity, type or even presence of
motor speech disorders needs further study. The main objective of this study was to
investigate DDK rate, DDK accuracy (TA & CO), reading rate, and intelligibility in
speakers with PD.
7
Methodology
Subjects
The speech samples were previously obtainedfroma project investigating
suprasegmental features in Cantonese dysarthric speakers (Whitehall, Ciocca & Yiu,
1999). Eleven speakers with PD (9 males, 2 females) who demonstrated speech
problems based on perceptual judgment served as speaker subjects. The age range
was 43 to 78 years (mean: 63.8 years). Ten speakers were native Cantonese speakers,
whereas one speaker spoke Cantonese, Mandarin and Fukinese. This speaker's
Cantonese was judged not to be affected by his other dialects. All speakers passed
an aphasia screening test adaptedfromthe Cantonese Aphasia Battery (Yiu, 1992).
All speakers could read Chinese and had adequate vision. Nine passed a hearing
screening test presented at 20dB HL at frequencies of 500, Ik, 2k, & 4kHz. Two did
not complete the hearing screening, but their hearing was judged to be sufficient for
the experimental tasks. Six inexperienced listeners were recruited in the study for
the sentence intelligibility task. The subjects had normal hearing, and had Cantonese
as their primary language.
Procedures
Speaker Data collection
a. DDK tasks
The subjects were asked to produce three monosyllables, /pa/, /ta /, and /ka/, and
the trisyllable /pataka/, as fast as possible on a single breath. Three trials of each
task were taken. Based on perceptual judgment, the fastest and most accurate
production among the three trials was selected for analysis (Wit et al., 1993).
b. Reading task
In the present study, we followed the definition of rate used by Turner & Weismer
8
(1993), in that both articulation time and pause time were included. The subjects
were asked to read a standardized passage, the Barbara Streisand passage (gg&jfe
Mff) at their habitual rate. The speakers repeated the words produced by the
clinician if they did not know or missed a word.
c. Sentence tasks
Cantonese Sentence Intelligibility Test (Lo, 1999) was used to assess the speech
intelligibility of the speakers. The speakers read aloud 22 sentences (two sentences
each of 5 to 15 words) selected at random from the master pool of sentence.
Recording
The recording was done in a quiet room. The speech productions of the
subjects were recorded using a digital audio tape (DAT) recorder (SONY TCD-D3
MK II) and a high quality microphone (Breul & Kjaer; type 4003) with microphone to
mouth distance of 10cm.
Editing
Nonspeech tasks
a. DDK rate
Data of DDK rate was stored on a personal computer. Motor Speech Profile
(ver. 1.0; model 5141, Kay Elemetrics, Lincoln Park, NJ) was used in the analysis.
b. DDK accuracy (TA& CO)
The speech data were stored in individualfileson a Apple Power Macintosh
computer for editing. Soimdscope software (ver 1.44; GW Instruments, Cambridge,
MA) was employed in editing. The data of DDK accuracy (TA) was then dubbed
from the computer onto a MiniDisc recorder (SONY MDS-JB940) for perceptual
analysis. DDK accuracy (CO) was analyzed by Soimdscope.
Speech tasks
9
a. Reading rate and sentence intelligibility
The speech data were stored in individualfileson a Apple Power Macintosh
computer for editing. The speech samples were digitized at a sampling rate of
44.1kHz using Sound Designer software. The speech data were then dubbed onto a
MiniDisc recorder (SONY MDS-JB940) separately for analysis in listening tasks.
Analyses
a.
DDK rate
Thefirstfive seconds were selected for analysis, with the exclusion of the first
syllable, which might cause a speech onset effect, since it is usually produced with
longer duration (Ackermann et al., 1995). The DDK rate of each DDK train was
obtained by dividing the number of syllables produced by the elapsed time (5 sec).
The number of syllables produced was obtained by counting the number of peak
deflections from the visual display shown on the computer (one peak refers to one
syllable), using The Motor Speech Profile (ver. 1.0; model 5141, Kay Elemetrics,
Lincoln Park, NJ). Counting was supplemented by perceptual listening. For
example, if the judge calculated three peaks based on visual display, the judge listened
to the selected waveform portion of the three peaks to ensure three syllables were
produced. The mean rates of the three monosyllables and one trisyllable were used
to calculate the mean DDK rate.
b.
DDK accuracy
Articulatory accuracy of stop consonant production during DDK trains involved
two methods. The analysis involved only thefirstseven stop consonants of each
monosyllabic train (Ackermann, Hertrich & Hehr, 1995), and thefirstthree
trisyllables.
/. DDK accuracy (TA)
10
DDK accuracy (TA) refers to the ratio of number of correct productions of target
phonemes (/p, t, k/) to the total number of phonemes produced in monosyllabic and
trisyllabic trains. Omissions or substitutions of target phonemes with the other
phonemes were counted as incorrect productions. The perceptual analysis was done
by two fourth-year students of speech and hearing sciences
II
DDK accuracy (CO)
DDK accuracy (CO) refers to the ratio of number of complete closures of all
phonemes to the total number of phonemes in monosyllabic and trisyllabic trains.
Incomplete closures of stop consonants are thought to reflect undershooting of the
articulatory movements. According to Ackermann & Ziegler (1991), "incomplete
closures resultingfromreduced extension of the mandibular, labial, or lingual
movements orfromreduced occlusive force may be expected to result in an increase
of sound pressure during stop realization" (p. 1094). Complete closures are
represented by the appearance of decreased signal amplitude in the oscillogram
together with the absence of an audible air-stream (Ackermann, Hertrich & Hehr,
1995, Weismer 1984). The method used in the present study was a modification of
the method described by Ackermann, Hertrich & Hehr (1995) and Weismer (1984),
where the use of spectrogram was used as well. Complete closures were defined as
areas between the end of a syllable and the burst of the next syllable, when no energy
was shown in the spectrogram between 2000Hz and 4000Hz within a 10ms period,
and there was an obvious decrease of signal amplitude shown on the oscillogram
during this 10ms period. This method was supplemented by perceptual judgment
c.
Reading rate
Reading rate was calculated by dividing the number of syllables produced by the
reading time (Turner & Weismer, 1993). Reading time was calculated by subtracting
11
the time of the onset offirstsyllable by the time of the offset of the last syllable, using
a computer program (Sound Designer Software) to assist with time calculations.
The number of syllables that the speaker produced was counted perceptually.
Portions where the clinicians spoke were cut. Judges only had to identify the
omissions and additions in readings and then adjusted the syllables count.
d.
Sentence intelligibility
The Cantonese Sentence Intelligibility Test is similar in construction and
administration to the CAIDS (Yorkston, Beukelman & Traynor 1984). Each listener
heard two hundred and forty-two sentences (22 sentences eachfromeleven speakers).
Three minidiscs were prepared for the listening task. Each minidisc was listened to
by two listeners; speech samples were randomized manually for each disc. 24
sentences were repeated for intra-judge reliability. Before the task began, the
listeners heard ten sample sentences which were not counted in the analysis, it was
hoped this would decrease listeners' adjustment time to the task (Lo, 1999). The
listening was done in a quite room. The intensity level of the speech samples was
adjusted to a comfortable level by each listener. The listeners heard each sentence,
then orthographically transcribed the sentences. Pausing to write down the sentences
was allowed. The listeners could hear each sentence twice, but not more than two
times. Guessing at the words that listeners were uncertain of was encouraged. The
listeners were recommended to have a rest when necessary in order to maintain their
concentration level
Sentence intelligibility was calculated by dividing the number
of words correctly transcribed by the total number of words for all sentences. The
intelligibility scores were obtained by taking the mean scores across intelligibility
scoresfromthe six listeners.
Statistical analysis
12
The correlations between all measures were done either by Pearson's product
moment or Spearman Rank Correlation Coefficients. The decision for using
parametric or nonparametric statistical procedures was made separately for each
correlation. Parametric statistical procedures (Pearson's correlation coefficients)
were employed when heterogeneity of variance was acceptable, and when the
criterion of normal distribution was met, as determined by Kolmogorov-Smirnov
single-sample test.
Results
Reliability
Pearson's correlation coefficient was used to determine all inter- and intra-judge
reliabilities. For sentence intelligibility, interjudge reliability was obtained between
pairs of judge's scores. The interjudge and intrajudge correlation coefficients for all
pairs of judge were strongly significant (see Appendix A and B). Interjudge
reliability coefficients ranged from 0.85 to 0.97. Intrajudge reliability was obtained
by the listeners rewriting 24 sentences selected randomly from the samples. The
correlation coefficients rangedfrom0.9 to 0.98.
For DDK accuracy (TA), the inter-judge reliability was obtained by measuring
all the speakers' samples whereas intra-judge reliability was obtained by calculating
two random selected speakers' samples. Both reliabilities were high (above 0.99)
(refer to Table 1 for details).
The interjudge and intrajudge reliability of DDK rate, DDK accuracy (CO) and
reading rate were calculated from two random selected speakers. For reading rate,
both the inter- and intra-judge had 100% agreements. For the DDK rate and DDK
accuracy (CO), both the inter- and intra-judge correlations were above 0.96 (refer to
Table 1).
13
Table 1. Inter- and Intra-iudse reliabilities of DDK rate. DDK accuracy (TA). and
DDK accuracy (CO) using Pearson's Correlation Coefficients
DDK rate
DDK accuracy (TA) DDK accuracy (CO)
Intra-judge
0.99**
1.0**
0.97**
Inter-judge
0.99**
0.99**
0.96*
°**p<0.0001 *p<0.0005
~~
"~
""~~"
—
-
DDK accuracy (TA)
The mean DDK accuracy (TA) was 87.54% and the standard deviation was 18.09.
The percentages scores ranged from 53.3 to 100 (refer to Table 4). However, nearly
half of the speakers (5/11) had 100% accuracy.
DDK accuracy (CO)
The mean DDK accuracy (CO) was 44.67% and the standard deviation was
35.98. A large range of percentage scores was obtained which varied from 0 to 90%
(refer to Table 4). Every speakers exhibited incomplete closures, and only two
speakers had DDK accuracy (CO) above 90%.
DDK rate
All subjects produced the target DDK trains, except speaker 1 and 7, who did not
produce DDK trains of/ka/ and /pataka/, respectively. The mean and standard
deviation of duration of overall DDK trains were 4.84 and 1.79 respectively (refer to
Table 2 & 4 for details). The subjects showed a large range of mean DDK rates
varying from 1.47 to 7.81.
Subject data was compared with normative data (Tiffany,
1980) for both monosyllables and trisyllables trains. The mean rates for most
speakers (9/11) were lower than the mean rates for nondysarthric speakers. One
subject (subject 9) had rate similar to the norms and one subject (subject 10) had a
higher rate.
Significant correlations between DDK rates of/pa/, Hat, /ka/ and
/pataka/ were also found (refer to Table 3). This suggested a high degree of internal
consistency in DDK rate performance; there is a tendency for those who have slow
14
rate on one syllable to have slow rate on the other syllables.
Subject
DDK rate
DDK rate
(ka)
1
(pa)
5.61
DDK rate
(ta)
5.76
DDK rate
(pataka)
5.81
Overall DDK
rate
5.73
2
4.8
4.31
3.98
4.80
4.47
3
5.17
5.79
4.99
3.60
4.89
4
4.20
3.40
3.70
3.99
3.82
5
4.60
4.57
4.81
4.58
4.64
6
1.40
4.66
2.2
3.01
2.82
7
5.19
4.89
4.41
8
0.80
1.80
1.30
2.00
1.47
9
7.19
6.81
6.58
7.60
7.05
10
8.00
8.05
7.39
7.80
7.81
11
6.00
6.59
5.00
5.18
5.69
4.81
Mean rate
(syllables/sec)
MeanSJD.
2.15
5.15
4.44
4.84
4.84
1.72
1.82
1.86
1.79
7.1
6.2
7.5
Norms*
7.1
Notes: DDK=diadochokinesis
4.83
*from Tiffany (1980).
Table 3. Relationship between individual monosyllables, trisyllables and mean DDK
rate, using Pearson's Correlation Coefficients
/pa/
/ta/
0.86**
/ka/
0.98***
/pataka/
0.92**
Mean DDK 0.98***
rate
*p<0.05
**p<0.001
/ta/
/ka/
0.90**
0.84*
0.93***
0.93***
A QQ**#
***p<0.0001
15
/pataka/
0.96* * *
Mean DDK
rate
Reading rate
Readmg rate across 11 speakers ranged from 1.33 to 3.63 syllables per second.
The mean reading rate (syllables per seconds) was 2.37 syllables per second and the
standard deviations was 0.63 (refer to Table 4). Most speakers (8/11) had reading
rates between 2 and 2.9 syllables per second; only a few exhibited significantly low or
high rates.
Sentence Intelligibility
The mean intelligibility score was 90.08 with a standard deviation of 6.78.
The
speakers showed a limited range of severity with percentage scores ranging from 76.8
to 98.3% (refer to Table 4). About 64% (7/11) of speakers had intelligibility scores
above 90%.
Table 4. Skeleton table of the data collection
Subject
1
MeanDDK Readmg rate DDKaccuracy DDKaccuracy Sentence
rate (syll/sec) (syll/sec)
(TA)(%)
(CO) (%)
intelligibility(%)
89.9
56.7
0
5.73
2.32
2
4.47
2.94
96.7
90
92.5
3
4.89
2.24
100
90
98.3
4
3.82
2.79
96.7
53.3
88.7
5
4.64
3.63
100
40
92.0
6
2.82
2.00
86.21
0
94.5
7
4.83
1.33
100
71.43
95.0
8
1.47
1.57
53.3
0
78.0
9
7.05
2.53
100
60
93.5
10
7.81
2.40
100
73.3
91.7
11
5.69
2.32
73.3
13.3
76.8
Mean
4.84
2.37
87.54
44.67
90.08
S.D.
1.79
0.63
18.09
35.98
6.78
Notes: DDK rate=diadochokinetic rate, DDK accuracy (TA)=target accuracy, DDK
accuracy (CO)=complete occlusion.
16
Relationships between variables
All the relationships between DDK rate, DDK accuracy (TA & CO), reading rate
and sentence intelligibility were obtained using Spearman rank-order Correlation
Coefficients.
The results of all correlations are shown in Table 5.
Relationship between rate measures
There was no significant correlation between DDK rate and reading rate (rs =
0.17,p=0.61).
Relationship between DDK measures
There was no significant correlation between DDK rate and DDK accuracy (TA)
(rs =0.43, p=0.19) or between DDK rate and DDK accuracy (CO) (rs = 0.33, p= 0.33)
A moderate significant correlation was found between DDK accuracy (TA) and
DDK accuracy (CO) (rs=0.74, p<0.01).
Relationships with sentence intelligibility
There was no significant correlation between sentence intelligibility and DDK
rate (rs= 0.06, p=0.85).
There was no significant correlation between sentence intelligibility and reading
rates(rs=-0.18,p=0.59).
No significant correlation between sentence intelligibility and DDK accuracy
(CO) (rs=0.52, p=0.11) was found. A moderate correlation was found between
sentence intelligibility and DDK accuracy (TA) (rs=0.65, p<0.05)
Other Relationships
There was no significant correlation between reading rate and DDK accuracy
(TA) (rs=0.27, p=0.42) or between reading rate and DDK accuracy (CO) (rs=0.27,
p=0.43)
17
Table 5: Spearman's Correlation Coefficients of DDK rate, reading rate. DDK
accuracy (TA & CO) and sentence intelligibility
DDK rate Reading DDK
DDK
Sentence
rate
accuracy accuracy intelligibility
(TA)
(CO)
DDK rate
Reading rate
DDK accuracy (TA)
DDK accuracy (CO)
Sentence intelligibility
p<0.05
p<0.01
0.17
0.43
0.33
0.06
0.27
0.27
-0.18
CV-C .'5
0.52
Discussion
Folkins et al. (1995) stated that "we do not know which nonspeech tasks will
generalize to the control of speech until we test them" (p. 142). This study showed
that some nonspeech tasks can generalize to speech tasks but some cannot.
Moderate significant correlations were obtained between sentence intelligibility &
DDK accuracy (TA) (rs=0.65) and DDK accuracy (TA) & DDK accuracy (CO) (r,
=0.74). However, no significant correlations were obtained between DDK rate &
sentence intelligibility, DDK rate & reading rate, DDK rate & DDK accuracy (TA &
CO), reading rate and sentence intelligibility, reading rate & DDK accuracy (TA &
CO), & sentence intelligibility and DDK accuracy (CO). The results showed that the
nonspeech tasks (DDK rate and DDK accuracy [CO]) might not be good predictors of
speech tasks, at least for sentence intelligibility and reading rate.
The present study can be compared with the other studies investigating similar
correlations. No significant correlations were obtained between DDK rate and
sentence intelligibility in the present study. The current result was consistent with
Buck & Cooper (1956), who found no significant relationship between DDK rate and
18
articulator^ proficiency
But the present results were different from those obtained
by Canter (1965) and Dworkin & Aronson (1986). The differences in the results
may be due to the use of different experimental methods. First, a scaling method
was used in those studies to measure articulately proficiency or speech intelligibility,
Sentence intelligibility using direct transcription may be more reliable and more
sensitive to articulation deficits.
Although those studies was also intended to rate
intelligibility, whether the scores obtained from scaling procedures measuring
articulatory proficiency is truly a measure of 'intelligibility5 is doubted.
Potentially
variables like suprasegmental factors (pitch, prosody) are difficult to control
Scaling may represent a global judgment of severity of speech, unlike using direct
transcription in measuring sentence intelligibility.
seemed to have only mild intelligibility.
Second, the speakers in this study
The use of direct transcription may not be
sensitive enough in detecting subtle, small but real differences among the speakers
(Yorkston & Beukelman, 1980). Different intelligibility measuring methods might
be sensitive to different severity groups of patients (Yorkston & Beukelman, 1980).
Therefore, it is believed different methods in rating intelligibility used in previous
studies and in this study might contribute to the differing results. Third, the listeners
employed were different in terms of experience. In the studies of Canter (1965) and
Dworkin & Aronson (1986) study, intelligibility was rated by experienced speech
pathologists.
In the present study, naive speakers were employed.
As Beukelman
& Yorkston (1980) suggested, "speech pathologists may overestimate intelligibility
scores because they are more familiar with the speech patterns of dysarthric speakers
than unfamiliar speakers" (p.37). Therefore, the sentence intelligibility obtained in
the present study might even be higher if rated by experienced speech pathologists.
However, using naive listeners may have more value since the assessment of
19
intelligibility by them may be more representative of daily-life communication
(Barkmeier, Jordan, Robin & Schum, 1991).
No significant correlation was obtained between DDK accuracy (CO) and
sentence intelligibility. Thisfindingwas differentfromthe study of Ackermann &
Ziegler (1991), who found a significant correlation between perceived severity of
overall articulatory impairment and undershooting of articulatory gestures. Both
studies aimed tofindwhether articulatory imprecision correlates with intelligibility.
The inconsistency in results may be for several reasons: First, as explained above,
rating of articulatory performance, which is possibly less sensitive, was used by
Ackermann & Ziegler (1991). Second, undershooting of articulatory gesture was
measured in different contexts. Ackermann & Ziegler (1991) measured
undershooting of consonants in sentence, which had variable phonetic contexts
whereas the present study measured undershooting of consonants in DDK trains, the
phonetic contexts was restricted to vowel /a/. Therefore, different nature of contexts,
like the possibility of coarticulatory effects in sentences might affect articulatory
precision which may cause less undershooting. Apartfromcontext, different rates
might also account for the differences. Rate was controlled in the study of
Ackermann & Ziegler (1991), where both undershooting and intelligibility were
measured under the speaker's normal speaking rate. But rate was not controlled in
the present study, the speakers needed to speak quickly in DDK task, but not required
in reading sentences.
No correlation was found between DDK rate and reading rate in the present
study. Thefindingwas consistent with thefindingof Tiffany (1980) who found no
significant correlations between maximum repetition rate (including DDK rate) and
reading rate. In the present study, there was also no significant correlation between
20
DDK rate and reading rate (rs=0.17, p=0.61). Although Kreul (1972) found a
significant correlation between DDK rate and normal reading rate, only mild
correlation was found between DDK trains /pa/ and /ka/ with reading rates (r=0.48 to
0.50).
In the present study, nonspeech tasks (DDK rate and DDK accuracy [CO]) had
no significant correlations with speech tasks (sentence intelligibility and reading rate).
Significant correlations between speech and nonspeech tasks were found only for
DDK accuracy (TA) and sentence intelligibility. Canter (1965) suggested that if a
subject performs a nonspeech task poorly, then it is reasonable to suspect there is a
deficit in the motor control that will also affect speech production. However, in this
study, it seems that subsystem motor unit control in nonspeech task does not
necessary correspond with the control units of the speech system. This would
support the view that "one cannot use nonspeech motor tasks as a window into speech
motor control processes" (Weismer, cited in Folkins et al, 1995, p. 141). There are
several reasons for poor generalization of most of our nonspeech tasks to the speech
tasks.
First, speech tasks involve many possible combinations of movements of many
structures. Therefore, the movement of intact structures can usually compensate for
deficits in the movements of impaired structures (Folkins et al., 1995). Moreover,
deficits in the movements of impaired structures in the connected speech tasks can
also be compensated by other cues, like contextual and suprasegmental cues. For
example, Dongilli (1994) found that understandability of test words was better in
sentences than in isolation, showing the presence of additional infomiation increases
speech understandability. Also, the presence of various phonetic contexts in speech
may provide other compensations, like coarticulations. In contrast, no compensation
21
of the impaired movement can be found in DDK tasks, either by intact movement of
other structures or by contexts, because DDK only involves one (/pa, ta, ka/), or three
movements (/pataka/). This may explains the nonsignificant correlations between
DDK rate & sentence intelligibility and DDK accuracy (CO) & sentence intelligibility.
As shown in table 4, some speakers with low DDK rate (e.g. speaker 2,3,4,5,6,7,8)
and low DDK accuracy (CO) (speakers 1,4,5,6,8) still had fairly high intelligibility.
Although DDK is claimed to reflect articulatory impairments and neutral intactness of
the motor system (Robin et al., 1997), compensation in connected speech tasks may
overcome the articulatory deficits.
Second, the nonspeech tasks (DDK rate and DDK accuracy) are maximum
performance tasks used to assess the maximum rate and range of repetitions in
syllabic sequences. However, "very few speech task call forth full diadochokinetic
ability "(Lundeen, 1950, p.58). Also, as Kent, Kent, & Rosenbek (1987) point out,
maximum measures might not be relevant to natural speech since "speaking under
ordinary circumstances does not tax the performance capabilities of the speech
system" (p.382). Folkins et al. (1995) and Soloman, Robin & Luschei (2000)
pointed out that subjects with poor performance in nonspeech tasks may still perform
many speech tasks accurately since the normal ranges of oromotor structures and
functions in speech is much smaller than in nonspeech tasks. It is interesting to note
that one speaker (speaker 8) who had the slowest DDK rate and lowest DDK accuracy
(CO) had comparatively low intelligibility score and reading rate. Perhaps
significant problems in connected speech could only be observed when a critical level
of deficit in the performance of nonspeech tasks (DDK rate and DDK accuracy [CO])
is obtained. However, two speakers (1 & 6) with very low DDK accuracy (CO) (0%)
but comparatively faster DDK rate (compared with the slowest DDK rate) had high
22
intelligibility. Perhaps poor performance in intelligibility may only occur when there
is both slow DDK rate and low DDK accuracy (CO). This might explain why poor
intelligibility is seen in speaker 8, but not speakers 1 & 6. Multivariate analysis
techniques may be important in studying the relationship between speech and
nonspeech tasks.
Third, DDK is different from natural speech in that DDK trains are composed of
repetitive syllables or trisyllables. Speech is not just composed of simple sequences
of sound, but consists of always changing prosodies involving complex, simultaneous
articulations (Tiffany 1980). This might further account for the nonsignificant
correlations between DDK rate and reading rate.
Fourth, the nonspeech tasks used in this study (DDK rate and DDK accuracy) may
not tap the control processes of speech tasks (sentence intelligibility and reading rate).
Moore, Smith & Ringel (1986) proposed that the control strategies for orofacial
structures in nonspeech tasks may be different from those required for speech. More
specifically, they reported that there were different EMG activation patterns ofjaw
activity in nonspeech and speech tasks. It is believed nonspeech tasks that mimic the
control processes of speech are more likely to generalize to speech tasks (FolMns et
al, 1995; Barlow & Netsell, 1986). Therefore, the significant correlation of DDK
accuracy (TA) with sentence intelligibility may be explained by the motor process in
these two tasks being closer.
Clinical Implications
DDK, has been regarded as useful nonspeech assessment tool in motor speech
disorders. In the present study, we have found no significant correlation between
DDK and the speech tasks of sentence intelligibility and reading rate. In contrast,
DDK accuracy (TA) had a positive correlation with sentence intelligibility.
23
Increasing attention should be placed on the use of DDK accuracy (TA) as an
assessment tool in motor speech disorders in clinical practice. Although DDK rate
and DDK accuracy (CO) have little predictive value for sentence intelligibility and
reading rate, it still has its importance in the diagnosis of the motor speech disorders
(Canter, 1965; Ackermann, Hertrich & Hehr, 1991). Also, it aids in examining the
subsystem of speech motor system, it helps tofindout the underlying primary motor
impairment, eliminating the possibility of compensation of the impaired structure by
the other structures in speech tasks (Wit, Maassen, Gabreels & Thoonen, 1993). In
sum, the combined use of nonspeech and speech tasks in the assessment of motor
speech disorder is essential to understand the integrity of speech motor system.
Further Investigation
In this study, as most of the speakers had high intelligibility scores, the results
are more likely to be representative for the mild group of speakers with PD only.
Therefore, it is recommended that a wider range of severity of speakers should be
examined in the future studies.
Further investigation between other nonspeech tasks and other speech tasks in a
variety of neurological groups is suggested. In order to find more stronger
correlations, selection of nonspeech tasks that are closer to the motor requirements of
the speech task is suggested (Folkins et al, 1995; Barlow & Netsell, 1986). For
example, modifications of DDK tasks can be made with producing the movement at
rate and force similar to speech-tasks. Also, different kinds of intelligibility, such as
word intelligibility is suggested. In this way, the factor of compensation by
providing contextual cues in sentence intelligibility can then be eliminated.
Finally, ongoing investigation on the 'threshold5 of weakness in nonspeech task,
together with multivariate analysis, is suggested, with the hope that simple nonspeech
24
motor tasks may make great contributions to our understanding of assessment in
motor speech disorder in the future.
References
Ackermann, ft, Grone, B.F., Hoch,G, & Schonle, RW. (1993). Speech
freezing in Parkinson's Disease: A kinematic analysis of orofacial movement by
means of electromagnetic articulography. Folia Phoniatrica, 45, 84-89.
Ackermann, H., Hertrich, L, & Hehr, T. (1995). Oral diadochokinesis in
neurological dysarthrias. Folia Phoniatrica et Logopaedica, 47,15-23.
Ackermann, H., & Ziegler, W. (1991). Articulatory deficits in Parkinsonian
dysarthria: An acoustic analysis. Journal ofNeurology, Neurosurgery, and
Psychiatry, 45, 1093-1098.
Andrews, G., Piatt, L.I, & Young, G. (1977). Factors affecting the
intelligibility of cerebral palsied speech to the average listeners. Folia Phoniatrica,
29, 292-301.
Barkmeier, J., Jordan, L.S., Robin, D.A., & Schum, R.L. (1991). Inexperienced
listener ratings of dysarthric speaker intelligibility and physical appearance. In C.
Moore, K.M. Yorkston & D.R. Beukelman (Eds.), Dysarthria andapraxia ofspeech:
Perspectives on management (pp. 15-27). Baltimore: Paul H. Brookes.
Barlow, S. W., & Netsell, R. (1986). Differential fine force control of the upper
and lower lip. Journal ofSpeech and Hearing Research, 29, 163-169.
Beukelman, D.R., &Yorkston, K.M. (1980). Influence of passage familiarity on
intelligibility estimates of dysarthric speech. Journal of Communication Disorders,
13, 33-41.
Buck, I E , & Cooper, IS. (1956). Speech problems in parkinsonian patients
undergoing anterior choroidal artery occlusion or chemopallidectomy. Journal ofthe
American Geriatric Society, 4, 1285-1290.
Canter, G.J. (1963). Speech characteristics of patients with parkinson's disease:
26
I. intensity, pitch, and duration. Journal of Speech and Hearing Disorders, 28,
221-229
Canter, G.J.
(1965).
Speech characteristics of patients with Parkinson's
disease: HI. Articulation, diadochokinesis, and over-all speech adequacy. Journal of
Speech and Hearing Disorders, 30, 217-224.
Darley, F.L., Aronson, A.E., & Brown, J.R.
(1975). Motor Speech Disorders.
Philadelphia: WB Saunders.
Dongilli, P.A, Jr. (1994). Semantic context and speech intelligibility.
In J. Till,
K.M. Yorkston, & D.R. Beukelman. (Eds.), Motor speech disorders: Advances in
assessment and treatment (pp. 175-191). Baltimore: Paul H. Brookes.
Duffy, J.R. (1995), Motor speech disorders: substrates, differential diagnosis
and management. St Louis: Mosby.
Dworkin, P.J., & Aronson, A.E. (1986). Tongue strength and alternate motion
rates in normal and dysarthric subjects. Journal of Communication Disorders, 19,
115432.
Folkins, J.W., Moon, J.B., Luschei, E.S., Robin, D.A., Tye-Murray, N. & Moll,
KX. (1995). What can nonspeech tasks tell us about speech motor disorders.
Journal of Phonetics, 23, 139-147.
Forrest, K., & Weismer, G. (1997). Acoustic analysis of dysarthric speech. In
M.R. McNeil (Ed.), Clinical management of sensorimotor speech disorders (pp.
63-80). New York: Thieme.
Kent, R.D., Kent, J.R, & Rosenbek, J.C. (1987). Maximum performance tests
of speech production. Journal of Speech and Hearing Disorders, 52, 387-387,
Kreul, EX (1972). Neuromuscular control examination (NMC) for
parkinsonism: Vowel prolongations and diadochokinetic and reading rates. Journal
27
of Speech and Hearing Research, 15, 72-83.
Lo, A.C-Y (1999). Intelligibility and acceptability measurement of Cantonese
dysarthric speech. Unpublished undergraduate dissertation. Hong Kong: The
University of Hong Kong, Department of Speech and Hearing Sciences.
Ludlow, C.L., Connor, N.P., & Bassich, C J. (1987). Speech timing in
Parkinson's and Huntington's disease.
Brain and Language, 32, 195-214.
Lundeen, D.J.(1950). The relationship of diadochokinesis to various speech
sounds. Journal of Speech and Hearing Disorders, 15, 54-49.
Luschei, E.S. (1991). Development of objective standards of nonspeech oral
strength and performance: An advocate's views. In C. Moore, K.M. Yorkston, &
D.R. Beukelman (Eds.), Dysarthria andapraxia of speech: perspectives on
management (pp 15-27). Baltimore: Paul H. Brookes.
Moore, C.A., Smith, A., & Ringel, R.L. (1988). Task-specific organization of
activity in human jaw muscles. Journal of Speech and Hearing Research, 31,
670-680.
Robin, D.A., Solomon, N.R, Moon, J.B., & Folkins, J.W. (1997). Nonspeech
assessment of the speech production mechanism. In M.R. McNeil (Ed), Clinical
management of sensorimotor speech disorders (pp. 49-62). New York: Thieme.
Schiavetti, N. (1992).
intelligibility.
Scaling procedures for the measurement of speech
In R.D. Kent (Ed.), Intelligibility in speech disorders. Philadelphia:
John Benjamins Publishing Company.
Solomon, N.P., Robin, D.A., & Luschei, E.S. (2000). Strength, endurance, and
stability of the tongue and hand in parkinson disease. Journal of Speech, Language
and Hearing Research, 43, 256-267,
Tiffany, W.R. (1980). The effects of syllable structure on diadochokinetic and
28
reading rates. Journal of Speech and Hearing Research, 23, 894-908.
Tjaden, K. (2000). A preliminary study of factors influencing perception of
articulatory rate in parkinson disease. Journal of Speech, Language and Hearing
Research 43, 9974010.
Turner, G.S., & Weismer, G. (1993). Characterises of speaking rate in the
dysarthria associated with Amyotrophic Lateral Sclerosis,
Journal of Speech and
Hearing Research, 36, 1134-1144.
Weismer, G. (1984). Articulatory characteristics of parkinsonian dysarthria:
Segmental and phrase-level timing, spirantization, and glottal supraglottal
coordination.
In M.R. McNeil, J.C. Rosenbek & A.E. Aronson (Eds.), Dysarthrias:
Physiology, acoustics, perception, management (pp 101-129). San Diego:
College-Hill Press.
Weismer, G., & Liss, J.M. (1991). Reductionism is a dead-end in speech
research: Perspectives on a new direction. In C. Moore, K.M. Yorkston & D.R.
Beukelman (Eds.), Dysarthria andapraxia of speech: Perspectives on management
(ppl5-27).
Baltimore: Paul H. Brookes.
Whitehill, T.L., Ciocca, V, & Yiu, E.M-L. (1999). Suprasegmental contributors
to intelligibility and acceptability judgments of Cantonese dysarthric speech. Hong
Kong Research Grants Council.
Wit, J., Maassen, B., Gabreels, FJ.M.& Thoonen, G. (1993). Maximum
performance tests in children with developmental spastic dysarthria. Journal of
Speech and Hearing Research, 36, 452-459.
Yiu, E.M-L. (1992). Linguistic assessment of Chinese-speaking aphasics:
Development of a Cantonese Aphasia Battery. Journal ofNeurolinguistics, 7,
379-424.
29
Yorkston, K M , Beukelman, D.R. & Traynor, CD (1984). Computerized
Assessment of Intelligibility of Dysarthric Speech. Austin, TX: Pro-ED.
Yorkston, KM, Dowden, P., & Beukelman, D.R. (1992). Intelligibility
measurement as a tool in the clinical management of dydarthric speakers. In R.D.
Kent (Ed.), Intelligibility in speech disorders: Theory, measurement, and management
(pp. 265-285). Philadelphia: John Benjamins.
Yorkston, K.M. & Beukelman, D.R. (1980). A clinician-judge technique for
quantifying dysarthric speech based on single-word intelligibility. Journal of
Communication Disorders, 13,15-31.
30
Appendix A: Interiudge reliability of sentence intelligibility using Pearson's
Correlation Coefficients
Judges
1
1
2
3
4
5
6
2
3
4
5
6
Mean scores
0.69
0.86
0.72
0.77
0.77
0.88
0.76
0.96
0.79
0.81
0.80
0.85
0.81
0.94
0.91
0.85, p<0.001
0.94,p<0.0001
0.88,p<0.0005
0.92, p<0.0001
0.97, pO.OOOl
0.96, pO.0001
AppendixB: Intrajudge reliability of sentence intelligibility scores using Pearson's
Correlation Coefficients
Judges
1
1
2
3
4
5
0.97
2
3
4
5
6
0.92
0.97
0.98
0.90
6
0.98
All correlations significant at p<0.0001
31