University of Washington Working Papers in Linguistics Volume XX (200X) pp. x-y Spectral Vowel Reduction in Japanese Setsuko Shirai [email protected]1 Introduction In this paper, I will argue for spectral vowel reduction in the Japanese language. Although vowel reduction has been discussed in many languages, few studies have been conducted in Japanese. Since Japanese does not have stress contrast, it is reasonable to assume that no spectral vowel reduction occurs in Japanese. However, the research conducted by Wright (2003) revealed that lexically conditioned reduction occurred even on stressed vowels in English. Thus, it is possible that spectral vowel reduction may occur in Japanese as well. Furthermore, I speculate on whether duration is the sole determinant of spectral vowel reduction or there may be reduced vowel targets as well. 1.1 Background Spectral vowel reduction has been discussed for the last few decades. One issue is whether vowel reduction is centralization or vowel undershoot. Research conducted by Moon and Lindblom (1994) looked at direction of vowel formant displacement. In their study F2 of front vowels in the context of w_l moved toward the vowel periphery, indicating that vowel reduction was vowel undershoot. Another question is that is the degree of vowel reduction determined solely by duration? Lindblom (1963) hypothesized that duration was the determinant of spectral vowel reduction. Nord (1986) compared the F2 of stressed initial vowels with the F2 of unstressed final vowels, and concluded that duration was not the sole determinant of spectral vowel reduction. The results of the research conducted by van Bergem (1993) showed that onset and offset of reduced vowels did not coincide with those of full vowels. He concluded that spectral vowel reduction was due to increased contextual assimilation.
Transcript
University of Washington Working Papers in Linguistics
Volume XX (200X) pp. x-y
Spectral Vowel Reduction in Japanese Setsuko Shirai
In this paper, I will argue for spectral vowel reduction in the Japanese language.
Although vowel reduction has been discussed in many languages, few studies have
been conducted in Japanese. Since Japanese does not have stress contrast, it is
reasonable to assume that no spectral vowel reduction occurs in Japanese. However,
the research conducted by Wright (2003) revealed that lexically conditioned reduction
occurred even on stressed vowels in English. Thus, it is possible that spectral vowel
reduction may occur in Japanese as well. Furthermore, I speculate on whether
duration is the sole determinant of spectral vowel reduction or there may be reduced
vowel targets as well.
1.1 Background
Spectral vowel reduction has been discussed for the last few decades. One issue is
whether vowel reduction is centralization or vowel undershoot. Research conducted
by Moon and Lindblom (1994) looked at direction of vowel formant displacement. In
their study F2 of front vowels in the context of w_l moved toward the vowel
periphery, indicating that vowel reduction was vowel undershoot.
Another question is that is the degree of vowel reduction determined solely by
duration? Lindblom (1963) hypothesized that duration was the determinant of
spectral vowel reduction. Nord (1986) compared the F2 of stressed initial vowels
with the F2 of unstressed final vowels, and concluded that duration was not the sole
determinant of spectral vowel reduction. The results of the research conducted by
van Bergem (1993) showed that onset and offset of reduced vowels did not coincide
with those of full vowels. He concluded that spectral vowel reduction was due to
increased contextual assimilation.
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1.2 Hypothesis 1: vowel centralization
The Japanese vowels, /a/, /e/, and /o/ in function words will be spectrally reduced
compared to content vowels.
2 Experiment 1: vowel centralization
2.1 Tokens
In the experiment, I compared three function vowels /a/, /e/, and /o/ in particles with
content vowels. These vowels were embedded in two pairs of sentences. Japanese
function particles are similar to English prepositions but are postpositions. Function
particles used in this experiment were subject marker /ga/, conjunction /to/, and /de/,
which indicated the place of action or served as copula. Adjacent phones, the number
of syllables in a word, and the position in a sentence were controlled.
(1) tokens [ga]: two-syllable word
a. bokushi, kiga kikitsukeru (content).
b. katou_san_wa ki_ga kiku (function).
[ga]: four-syllable word
c. nakamura_san_wa jinbutsuga toku_ni osukide irasshaimashita
(content).
d. ano eiga_wa jinbutsu_ga toku_ni yoku byousha sareteimasu
(function).
[to]: two-syllable word
e. hato kubi_o mawashita (content).
f. ha_to kuki dake shika nai (function).
[to]: three-syllable word
g. kookoosei kogoto karuku kikinagusu (content).
h. kookoo_no kogo_to kanbun_wa muzukashii (function).
[de]: three-syllable word
i. kotowaza_ni, tade kuu mushi mo suki dzuki to (content).
j. taue_no ato ta_de kuu meshi_wa umakatta (function).
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[de]: three-syllable word1
k. suizoku_kan_ni iku_made, hitode, kon’nani kireidanante
shiranakatta (content).
l. kato_san_wa, Tokyo no hito_de, korokoro_to yoku waratte,
aisoo_ga ii (function).
2.2 Procedure
Subjects were twelve Tokyo dialect speakers (six male and six female). Most were
their 20’s, and ESL students who had been in Seattle less than a year.
The subjects read five pseudo-randomized lists, of which three were used for
measurements, in the sound attenuated recording booth in the phonetics lab at the
University of Washington. The recordings were made using an Electro-Voice RE20
microphone with a flat response to 20 KHz, an amplifier (Shure model FP32A) and
an analog cassette tape recorder (TASCAM 122MK III). After the recording, the
speech was digitized at 44100 Hz, 16 bits, using Sound Edit 16 version 2 on a
computer equipped with an Audiomedia III card. The files were then the down-
sampled to 11, 025 Hz.
F1 and F2 at mid-point of target vowels were measured. In addition, F1 at the
vowel onset, 1/4, 1/2, 3/4 and vowel offset were measured to draw trajectories. The
formula used to measure change in F1, ∆F1, is calculated as follows:
∆F1 = F1 at mid-point – F1 at the beginning
Since vowel onset in function words was different from that in content words,
∆F1 was used to investigate the amount of tongue excursion.
3 Results 1: vowel centralization
The averages of the mid-point measurements are plotted in Figure 1, a vowel plot
showing F2 (horizontal axis) by F1 (vertical axis) values with Bark scaling. The
graph illustrates that F1 of function /a/ is evidently lower than content /a/.
1 Because of palatalization, Japanese [hi] is [i]. For the convenience I use [hi]. Japanese /u/ is unrounded [].
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Figure 1 “Plot Formants” illustrates the averages of formants. This graph is plotted based on the averages of raw data. Function vowels are expressed with small gray letters, and content vowels are large black letters.
Since the target syllables were /ga/, /to/ and /de/, spectral vowel reduction was
observed as centralization. The average graph showed that F1 of function /a/ was
noticeably lower than that of content /a/, but content /e/ and /o/ were overlapped with
function /e/ and /o/, respectively. Therefore, only function /a/ showed centralization.
The measurements have been summarized in Table 1 and plotted in Figure 2, box
plots showing the medians and ranges of F1 and F2 for all three vowels in both
content and function vowels.
Table 1 The average and standard deviation of individual vowels All Content Function
Figure 2 Box plot illustrates F1 and F2. The middle dark line in a box indicates the median (the 50th percentile). The length of a box represents the difference between the 25th and 75th percentiles. The length of a line (whisker) represents the difference between the 10th and 90th percentiles. The circles represent outliers.
In this experiment, F1 of /a/, F2 of /e/ and /o/ were relevant to the
centralization. The measures were submitted to a repeated measures ANOVA with
F1 and F2 as dependent variables and LEXICAL as an independent variable. The main
effect for LEXICAL on F1 for /a/ was [F(1, 65) = 73.401, p < 0.001], the main effect on
F2 for /e/ was [F(1, 68) = 3.549, p = 0.067] and the main effect on F2 for /o/ was [F(1,
71) = 1.150, p = 0.287]. Therefore, there was a significant lexical effect on F1 of /a/,
but was no significant lexical effects on F2 of /e/ and /o/. The results of the Post Hoc
Bonferroni-Dunn test with α level 0.05 showed F1 of function /a/ was significantly
lower than that for content /a/. Although there were no significant results for F2 of /e/
and /o/, the averages indicate that there is the tendency towards centralization.
4 Discussion 1: vowel centralization
The results indicated that function /a/ was noticeably more centralized than content /a/
but there was only subtle difference for /e/ and /o/. Although Japanese does not have
stress contrast, function vowels were centralized.
I will now speculate about the unexpected results for /e/ and /o/. The onsets of
/e/ and /o/ were /d/ and /t/ respectively. These consonants have been known as little
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co-articulation effects on adjacent vowels; in other words, the locus target distance
(i.e. the distance between inherent formants of consonant and inherent formants of
vowels) was short. As a result, the magnitude of the lexical effect was not large
enough to show statistical difference.
Japanese function vowels were shorter than content vowels (Shirai, 2002), and
centralized. These facts raised a question: is the centralization solely attributed to
undershoot?
5 Hypothesis 2: undershoot or lexical effect?
If durational reduction is the source of spectral reduction, which is undershoot
(Lindblom, 1963), then differences in F1 will be linked to differences in duration. If
lexical difference is the source of spectral reduction and independent from durational
reduction, then differences in F1 will be observed in the absence of differences in
duration.
6 Experiment 2: undershoot or lexical effect?
In the second experiment, F1 of /a/ was used. To test whether or not there was lexical
effect in the absence of durational difference, durations were classified into 3
categories (short, medium and long) based on the percentile ranking2. In addition,
trajectories were used to test if F1 of function /a/ moved towards the target for F1 of
content /a/.
6.1 F1Trajectories
To get a picture of trajectories, duration and F1 of each point were calculated as
follows. Regarding duration, the whole durations for content /a/ and function /a/ were
averaged, and then the duration of each point (0, 1/4, 1/2, 3/4) was calculated.
Regarding F1, F1s of each point (0, 1/4, 1/2, 3/4, the whole) were averaged. The
results of the calculation were plotted in Figure 3, a scatter graph showing average F1
2 The durations of measures (both content and function) were ranked in ascending order, and then classified into 3 categories. Therefore, the ratio of content vs. function in each category varies.
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values at each point (vertical axis) by duration (horizontal axis). The trend lines (the
least square line order 2) have been added.
Trajectories of F1
400
450
500
550
600
650
700
750
0 20 40 60 80 100
Duration (ms)
F1 (H
z)
contentfunctioncontentfunction
Figure 3 Scatter graph illustrates trajectories of F1 /a/. This graph was plotted the based on the averages of F1 at each point and the average of duration. Diamonds represent content vowels, while crosses represent function vowels. Solid trend line (polynomial order 2) represents the trajectory of F1 content /a/ while dashed trend line represents the trajectory of F1 function /a/.
Figure 3 showed that the target of content /a/ appeared different from that of
function /a/, and that there was a gap between the onset of content /a/ and that of
function /a/.
6.2 Categorical Duration
In order to test whether or not there was a lexical effect in the absence of duration,
durations are classified into 3 categories. The averages of the F1 mid-point that are
split by lexical and categorical duration are plotted in Figure 4, an error bar graph,
showing the interaction between categorical durations (horizontal axis) and F1 mid-
point (vertical axis) values.
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Figure 4 Error bar graph illustrates the interaction between the F1 mid-point and categorical durations. Black lines represent content /a/ while gray lines represent function /a/. Error bars indicate the 95 % Confidence interval.
In Figure 4, F1s of function /a/ were lower than those of content /a/ in all three
categories. In addition, the line for content /a/ was parallel to the line for function /a/.
The results of a factorial ANOVA with F1 as dependent variable, and
LEXICAL and CATEGORICAL DURATION as independent variables have been
summarized in Table 2, indicating that there were significant effects for LEXICAL and
for DURATION, but there was no INTERACTION of the two.
Table 2 The results of a factorial ANOVA for F1 LEXICAL DURATION INTERACTION F[1, 126] F[2, 126] F[2, 126] F 12.639 4.232 0.889P 0.001 0.017 0.413
6.3 ∆F1 Trajectories
In the F1 trajectories, the change of F1 for content /a/ appeared different from that of
function /a/; in other words, the tongue for content /a/ seems to move further than that
for function /a/. In order to examine it, ∆F1 trajectories are plotted in Figure 5, a
scatter graph showing duration (horizontal axis) by ∆F1 (vertical axis) values. The
trend lines (the least square line order 2) have been added.
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Trajectories of deltaF1
0
50
100
150
200
250
0 20 40 60 80 100Duration (ms)
delta
F1
(Hz) content
functioncontentfunction
Figure 5 Scatter graph illustrates the trajectories of ∆F1. This graph was plotted based on the averages of ∆F1 at each point and the average of duration. Diamonds represent content vowels, while crosses represent function vowels. Solid trend line (polynomial order 2) represents the trajectory of F1 content /a/ while dashed trend line represents the trajectory of F1 function /a/.
Although the starting point of F1 for content /a/ was the same as the starting
point for function /a/, function /a/ appeared to move slowly. To test if there was a
lexical effect in the absence of duration, ∆F1 mid-points have been plotted in Figure 6,
an error bar graph illustrating the interaction between ∆F1s and categorical durations.
Figure 6 Error bar illustrates the interaction between ∆F1 mid-points and three categorical durations. Black points represent content ∆F1 while gray points represent function ∆F1.
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The graph in Figure 6 shows that ∆F1s for content /a/ were greater than those
for function /a/ in all three categories, and the line for content /a/ is almost parallel to
the line for function /a/.
The results of a factorial ANOVA with ∆F1 as dependent variable, and
LEXICAL and CATEGORICAL DURATION as independent variables were summarized in
Table 3, indicating that there were significant effects for LEXICAL and for DURATION,
but there was no INTERACTION of the two.
Table 3 The results of a factorial ANOVA for ∆F1 LEXICAL DURATION INTERACTION F[1, 126] F[2, 126] F[2, 126] F 13.236 16.568 0.368p < 0.001 < 0.001 0.693
7 Discussion 2: undershoot or lexical effect?
The results of the factorial ANOVA with F1, the trajectories, and Figure 4 indicated
that there was a lexical effect in addition to undershoot effect. Therefore spectral
vowel reduction was not tied to duration.
The results of the factorial ANOVA with ∆F1 showed that ∆F1 for function
/a/ was significantly less than that for content /a/. In other words, for function /a/, the
tongue did not move as much as for content /a/. Function words convey only
grammatical meaning, so listeners can understand meanings of sentences without
them. When listeners easily understand words, speakers tend to pronounce words
vaguely (Lindblom 1990). Since Japanese function-particles indeed can be omitted,
spectral vowel reduction occurred.
In the experiment conducted by Moon and Lindblom (1994), a subject showed
a clear difference between F2 // in citation-form and in clear-speech, and F2 // in
citation-form is closer to F2 of /w/. The tongue movement for citation-form was less
than that for clear-speech. In other words, the tongue moved further to create the
pronunciation in clear-speech than in citation-form. Thus, the amount of the tongue
movement is influenced by lexical status or speaking style.
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8 Conclusion
The data support the first hypothesis that spectral vowel reduction occurs in the
Japanese language. Vowel /a/ shows noticeable spectral vowel reduction while /e/
and /o/ do not show much difference. The data also support the second hypothesis
that spectral vowel reduction is independent from durational reduction. In this
experiment, I used function particles /ga/, /de/ and /to/ to test spectral vowel reduction.
Since available particles are limited, I could not test /u/ and /i/3. To generalize this
finding, vowels in different contexts such as clear-speech should be tested.
Selected References
Keating, P and Huffman, M. 1984. Vowel Variation in Japanese. Phonetica, 41,
191-207.
Lieberman, P and Blumstein, S. 1988. Speech Physiology, Speech Perception, and
Acoustic Phonetics. Cambridge: Cambridge University Press.
Lindblom, B. 1963. Spectrographic Study of Vowel Reduction. Journal of
Acoustical Society of America,. 35, 1773-1781.
Lindblom, B. 1990. Explaining Phonetic Variation: A Sketch of the H&H Theory.
In W. J. Hardcastle and A. Marchal (eds.), Speech Production and Speech
Moon, S.J, and Lindblom, B. 1994. Interaction between duration, context, and
speaking style in English stressed vowels. Journal of Acoustical Society of
America, 96, 40-55.
Nearey, T. M. 1978. Vowel – space normalization procedures and phone-preserving
transformations of synthetic vowels. Journal of Acoustic Society of America,
63, S5.
Nord, L. 1986. Acoustic Studies of Vowel Reduction in Swedish. Quarterly
Progress and status report, 4, 19-36.
3 There is another particle /ni/, whose onset possibly causes nasalization of the vowel /i/. Thus, I did not use it. The Japanese language has no particle that consists of /u/.
12
Van Bergem, D. R. 1993. Acoustic vowel reduction as a function of sentence accent,
word stress, and word class. Speech Communication, 12, 1-23.
Wright, R 2003 Lexical competition and reduction. Papers in Laboratory Phonology
VI. 75-87. Cambridge: Cambridge University Press.
APPENDIX - data
Formants for [kiga] content function subject F1 F2 F1 F2 kt 658.20 1399.09 568.05 1383.46 kt 565.59 1515.17 563.90 1385.25 kt 610.45 1437.17 614.66 1430.16 m2h 693.61 1380.60 605.18 1610.05 m2h 704.66 1411.12 634.27 1495.05 m2h 642.63 1404.12 614.12 1495.85 mh 498.32 1684.02 475.17 1705.51 mh 506.71 1673.87 505.72 1703.22 mh 545.11 1605.47 497.62 1720.00 ss 586.26 1385.96 465.29 1466.69 ss 659.16 1269.26 418.43 1411.90 ss 644.18 1278.47 441.24 1451.41 ta 629.07 1428.22 607.90 1416.48 ta 682.03 1209.20 639.85 1446.45 ta 648.47 1409.64 601.08 1367.75 ykm 631.10 1267.79 517.42 1436.45 ykm 615.60 1246.82 507.71 1430.93 ykm 677.35 1234.82 482.09 1499.37 at 877.24 1805.44 723.88 1864.43 at 867.46 1795.97 634.89 1762.97 at 825.65 1845.09 798.33 1680.86 ei 807.04 1698.35 799.09 1862.89 ei 809.77 1718.79 790.15 1684.35 ei 767.10 1550.64 795.66 1669.84 kn 787.97 1702.65 631.91 1261.41 kn 741.64 1880.13 631.87 1598.15 kn 669.35 1565.82 584.72 1408.28 ye 697.54 1492.24 653.40 1531.44 ye 675.70 1591.93 627.36 1503.85 ye 651.30 1468.79 661.47 1485.15 yt 640.92 1870.22 591.45 1872.07 yt 557.24 1976.88 577.02 1904.25
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yt 625.35 1901.65 600.40 1961.28 Formants for [jinbutsuga] content function subject F1 F2 F1 F2 kt 675.83 1276.12 559.26 1375.30 kt 630.70 1339.79 577.37 1379.72 kt 630.46 1306.60 656.13 1309.09 m2h 698.01 1320.86 603.00 1429.17 m2h 710.51 1362.63 608.60 1600.89 m2h 732.57 1320.74 647.30 1442.68 mh 580.03 1477.03 563.10 1427.29 mh 540.01 1473.21 544.87 1446.04 mh 653.91 1441.14 536.99 1440.11 ss 614.31 1228.18 611.26 1217.51 ss 652.58 1197.38 571.81 1238.89 ss 658.32 1203.88 501.94 1290.14 ta 590.24 1273.75 533.17 1428.55 ta 563.49 1376.63 506.85 1442.73 ta 734.46 1199.95 517.75 1372.34 ykm 682.27 1238.62 606.31 1265.91 ykm 691.18 1238.60 525.11 1352.10 ykm 687.22 1224.84 619.02 1206.09 at 881.79 1665.67 743.66 1636.28 at 895.22 1613.78 738.61 1568.72 at 808.28 1657.36 725.80 1637.13 ei 798.80 1634.86 833.33 1650.35 ei 819.72 1633.37 807.19 1626.27 ei 773.43 1618.48 799.25 1613.68 kn 805.66 1471.85 670.80 1599.85 kn 806.53 1519.37 602.84 1494.75 kn 777.18 1342.23 672.23 1637.21 ye 736.89 1397.54 539.45 1382.25 ye 706.16 1424.55 629.05 1496.40 ye 672.47 1464.84 628.18 1492.97 yt 885.87 1586.75 661.07 1644.86 yt 853.63 1661.55 499.90 1619.59 yt 805.74 1671.41 546.27 1611.04 Formants for [hitode] content function subject F1 F2 F1 F2 kt 448.88 1678.57 481.70 1719.08 kt 488.85 1630.62 503.61 1722.38
