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Interaction of high vowel devoicing and
syllabificationNINJAL,13October, 2016
Syllables andProsody Workshop
Shigeto Kawahara& JasonShawKeioUniversityandYaleUniversity
Introduction
What wewouldliketodo
• Japanesehighvowelsare“devoiced”insomeenvironments.
• Q1:Arethesevowelsdeleted?Oraretheydevoiced?
• Q2:Iftheyaredeleted,thenwhat’stheconsequenceformoraification/syllabification?
• (Q3:ifJapanesespeakershaveCVCsyllablesduetohighvoweldeletion,aretheysensitivetosyllable-relatedphonotacticrestrictions,possiblyprovidedbyUG:cf.Berent’s recentwork?)
• Weoffernewarticulatorydataonthetabletobearonthesequestions.
Japanese highvoweldevoicing
• The standard description: Highvowels aredevoicedbetween twovoiceless consonants.
• Anexample, [ʃutaisei] “willingness”.
• “Devoicing” is thetraditional term used. However,whether these vowelsaresimply devoiced ordeleted stillremain debated.
• Devoiced=oral gestures remain intactorreduced.• Deleted=oral gestures deleted.
Devoicingvs.Deletion?
• Aphonetic devoicing view:• Laryngeal gestures overlap to passively devoicevowels (e.g., Jun & Beckman 1993).
• Aphonological deletion view:• Và ∅ /[-voice] _____ [-voice] (Kondo 2000)• Or aphonological process induced by asetof
markedness constraints (Tsuchida 1997).
Laryngealtier:
Oraltier:
devoicing devoicing
ʃ u t
Orcoulditbeboth?
• Kawakami(1971)listsenvironmentswherethetargetvowelsaredeletedandwheretheyaredevoiced.
• ButKawakamigivesnoinstrumentalevidence.
• Whang(2014,2016)arguesthatvowelsaredeletedwhentheiridentitycanberecoveredfromtheprecedingconsonants.
• Forexample,thedevoicedvowelispredictably[u]after[ɸ], butitisnotafter[k].Onlyintheformerenvironmentcanthevowelbedeleted.
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Japanese laryngeal gestures
• In devoiced vowelcontexts, e.g., /kite/, thereisasingle laryngeal gestureof greatermagnitudethan asingle consonant gesture, c.f. /kide/(Fujimoto etal.2002)
Howaboutlingualgestures?
• However,thelingualgestureofdevoicedvowelsisunderstudied.
• Funatsu &Fujimoto(2011),asfarasweknow,istheonlyexception.TheyusedEMMA,EGG,andPGG.
• TheirEMMAresultsshowonlysmalldifferencesbetweenvoiced[i]anddevoiced[i](implying“devoicing”,not“deletion”).
• Buttheystudiedonlyonespeaker.Andonlyonepairofstimuli([kite]vs.[kide]),oneofwhosememberisarealword. 4repetitionsandnoquantitativeanalyses.
Summary ofpastwork
• ThelaryngealdataindicatethatdevoicinginJapaneseisactivelycontrolled.
• Acousticevidenceforpresence/absenceofalingualvowelarticulationhasbeenlargelyequivocal,withsomestudiesclaimingthevowelhasbeendeleted,whileothersclaimingthatitispresent.
• Deletion:Beckman1982;Beckman&Shoji1984;Kondo1997,2000.
• Devoicing: Jun&Beckman1993;Faber&Vance2001;McCawley1968.
• Bothpossible:Kawakami1971;Tsuchida 1997;Whang2014
Ourcontributiontothedebate
• Electromagnetic Articulography (EMA) data onthelingualarticulation ofvowelsinvoicedanddevoicedcontexts.
• Acomputational method forevaluating voweldeletion onthe basisofmovementkinematics(Shaw &Kawahara,submitted).
• Showingthat somecasesdoinvolvecasesofactualdeletion.
• SomeimplicationsforprosodicorganizationofJapanese(stillinprogress).
EMAExperiment
EMA experiment
• Record the articulatory dynamics of voiced vowelsand devoiced vowel counterparts.
• Apply Discrete Cosine Transform tofit theobserveddata.
• Use aBayesian classifier toevaluatethe likelihoodthatdevoiced tokens have alingual articulation.
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Materials (target words)Devoicing/deletion Voiced vowel
Entropy = 1.99 (W,K) masutaaマスター masuda益田
Entropy = 1.89 (w) hakusai 白菜 yakuzai 薬剤
Entropy = 1.46 ʃutaisei 主体性 ʃudaika主題歌
Entropy = 1.08 (W,K) ɸusoku 不足 ɸuzoku 付属
Entropy = 0.09 (W,K) katsutoki 勝つ時 katsudou 活動
10-15repetitions of thetarget wordsinthe carrier phrase: okee ______ toitte ‘Ok,say ______’. Participants were instructed tospeak as if they were making a requestof a friend. Interspersed with10wordslacking /u/
ApparatusMagnetic Field
Generatorsensorwires(toSCU)
sensor
shotgunmic
Stimulusdisplaymonitor
Sensor placement
Tongue Tip(TT) 1cm behind the tip
Tongue Blade(TB) half-waybetween the TD and TT sensors
Tongue Dorsum(TD) as farbackas comfortable forparticipant
Jaw sensor Additional sensors:Upper lip (UL)Lower Lip (LL)JawNasianLeft/Right mastoids
Lingualsensors
Procedure• Stimuliwerepresentedonamonitorinrandomorder.• Topromotefluentreading,targetwordswerepreviewedbeforedisplayedinthecarriersentence.
• AnativespeakerofJapanesemonitoredpronunciationmanuallyadvancingtrialsafteracceptingorrejectingeachtoken.
主体性 オーケー主体性と言って。
Target preview (500ms) Target sentence
Post-processing
• Headmovements corrected computationally• Datarotated totheocclusal (bite) plane
• Robust smoothing (Garcia 2010)
EMASensors
Acousticresults: voweldevoicingInlinewithcurrentdescriptionsofTokyo Japanese, /u/wasdevoiced between voicelessconsonantsandvoicedotherwise.
ɸu?s oku ɸuz o ku
/ɸusoku/ /ɸuzoku/
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Results: ɸusoku~ɸuzoku
e /u/
s/z
TD islowerfordevoicedvowel
VerticalPo
sition(m
m) o
TT riseisearlierfor/s/ than /z/
Time (ms)
S01
Tip
Blade
Dorsum
Red=devoicedBlue=voiced
Results: ʃutaisei~ʃudaika
e
a
/u/
ʃ
t/d
LowerTD andTBfor devoiecd
/u/
VerticalPo
sition(m
m)
Earlier TTgesturefor /t/than for /d/
S01
Results: hakusai~yakuzai
a /u/
s/z
TD islowerfordevoiced/u/
VerticalPo
sition(m
m)
a
TT riseisearlierafter the
devoiced/u/
kS01
Results: katsutoki~katsudou
a /u/
ts
TD islowerfordevoicedvowel
VerticalPo
sition(m
m)
o
TT releaseisearlierafter thedevoicedvowel
t/d
o
k
S01
Results: masutaa~masuda
TemporaldifferenceinTDrise;devoicedvowelislater
VerticalPo
sition(m
m)
a
a
/u/
d/t
aa
sAndTBrise;devoicedvowelislaterandhigher
S01
Computationalanalysis
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Analysis
• Voicing effect:do voiced and devoiced voweltrajectories differ?
• Phonological deletion: is thevowel /u/ absent inanyof thesewords?
• Discrete CosineTransform(DCT) onTDtrajectories• Simulate a“targetless” trajectory• Compare DCTcoefficients of“targetless” trajectory todata, c.f.,t-testagainst zero.
Discrete CosineTransform (DCT)ComplexcurverepresentedasthesumofCosines:
1st Cosine
2nd Cosine
3rd Cosine
intercept
Sum of cosines
𝐶 𝑚 cos( 𝜃)where mis the nthcosineand 𝜃 is a functionof length
𝐶 𝑚 = 2𝑁𝑘./ 𝑥 𝑛 cos
2𝑛+ 1 (𝑚− 1)𝜋2𝑁
678
9:;
Where N is the number of data samples;M = 1 ,…,N; 𝑘. =
8
<whenm = 1,else 𝑘. = 1 ;
x(n) isthe intercept;
HowmanyDCTcoefficients areneeded?• Nearly lossless compression (99.6%) with 6coefficients.
• Weused 4DCT coefficients (99.0%)
.996.990
EachcosinecomponentsRaw data (green)Mean DCT (black)[e]-to-[a] line(red)
1stDCT Coeff icientà Average TD height
2nd DCT Coeff icientà V-to-Vtrajectory
3rd DCT Coeff icientà Intervening vowel
4th DCT Coeff icientà Consonantal effects
ea
ea
u
dʃ ʃd
Voweldeletion(“noisynull”)trajectories
Noisy null trajectories (blacklines) generated fromstochastic sampling of Gaussian distributionsdef ined bymean DCTcoefficientsfit tothedirecte-to-atrajectory (redline)and thestandard deviationofDCT coefficients fittotheraw data (greenlines) .
e
a a
eraw data (greenlines)directe-to-atrajectory
(redline)
voiced voicelessWithin-speaker, within-word variation
S01
Some tokens lookmore like noisy null,whereas others looklike they have a cleartarget.
PhoneticreductionOrvariable deletion?
Almost alltokens lookpretty dif ferentfromnoisy null
Noisy null
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Token-by-tokenevaluation
𝑝(𝐷|𝑐8, . . . , 𝑐D) =𝑝 𝐷 𝑝(𝑐8 , . . . , 𝑐D |𝐷)
𝑝 (𝑐8, … ,𝑐D)
where...𝐷 ={deletion,fullvowel}𝑐8=1st DCTCoefficient𝑐< =2nd DCTCoefficient𝑐F =3rd DCTCoefficient𝑐G =4th DCTCoefficient
Fit a naïve Bayes classif ier tothedata andused it togenerate (posterior) deletion probabilities Trainingdata=
voicedtokens (fulltarget) &noisynull(notarget)Testdata=voicelesstokens
Simulated predictions
Posteriord
eletionp
robabilities
Deletion probabilities bytoken:/ɸusoku/(allspeakers)
Lessthan.1chanceofdeletion
Greater than .9chanceofdeletion
Posteriordeletionprobability
Note: DCTcoeff icients arespeaker-specif ic. Theresults are tallied.
Classificationparameters1stDCT
Coeff icient
2nd DCTCoeff icient
3rd DCTCoeff icient
4th DCTCoeff icient
Greatestseparationfor
3rd DCTcoefficient
/ɸusoku/
Parameters andprobabilities: /ʃutaisei/ (allspeakers)
Posteriordeletionprobability
1stDCT
2nd DCT
3rd DCT
4th DCT
Targetpresent
Targetabsent
Parameters andprobabilities: /katsutoki/(allspeakers)
Posteriordeletionprobability
1stDCT
2nd DCT
3rd DCT
4th DCT
Targetpresent
Targetabsent
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Parameters andprobabilities: /hakusai/(allspeakers)
Posteriordeletionprobability
1stDCT
2nd DCT
3rd DCT
4th DCT
Targetpresent
Targetabsent
Parameters andprobabilities: /masutaa/ (allspeakers)
Posteriordeletionprobability
1stDCT
2nd DCT
3rd DCT
4th DCT
Targetpresent
Targetabsent
AlltheresultsS01 S02 S03 S04 S05 S06 average
ɸusoku 0.47 0.39 0.75 0.84 0.01 0.19 0.44
ʃutaisei 0.92 0.68 0.84 0.99 0.02 0.89 0.72
katsutoki 0.81 0.19 0.69 0.93 0.06 0.79 0.58
hakusai 0.00 0.00 0.51 0.50 0.00 0.07 0.18
masutaa 0.64 0.09 0.01 0.02 0.74 0.41 0.32
average 0.57 0.27 0.56 0.66 0.17 0.47 0.45
• /ʃutaisei/ shows the highest probability of deletion; /hakusai/ the lowest.• S03 & S04 show high deletion probabilities; S05 barely showed deletion.
Effectofsurfaceconsonantclustertype?• Allthehistograms are bi-modal, supporting theoptional deletion hypothesis.
• Forallspeakerswe find:
ʃ_t >>ɸ_s >>k_s
ts_t
Implicationsforphonologicalorganization σ σ
μ μ
ʃ t a
Possibleconsequencesofdeletionσ σ
μ μ
ʃ u t a
σ
μ
ʃ t a
Resyllabif ication(Kondo2000)
Consonantal syll(Matsui 2015)
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Moraremains
• Abimoraic truncation pattern (Poser 1980 etseq.)counts moras of a“devoiced” vowelasmoraic(Kawahara 2015; Tsuchida 1997).
• E.g. [suto] <[sutoraiki] (loanword truncation)• E.g. [tʃika(-tʃaɴ)] <[tʃikako] (hypocoristic)• E.g. [ɸuka-ɸuka] (mimetics)
• Hirayama (2009) shows thatdevoiced vowels countasmuch asvoiced vowels forhaiku.
Syllableremains too(?) Ito(1990),Kawahara (2016)
= a wordmustbe bisyllabic;Wd much branch( I&M 1992)
= a devoiced vowel projects its syllable
Syllableremains too(?)
• Predictions from the cross-linguistic perspectives:
σ
μ
ʃ t a
σ σ
μ μ
ʃ t aRising sonority is better; a.k.a.Sonority Sequencing Principle(SSR)
Falling sonorityis better; a.k.a.Syllable Contact Law (SCL)
Effectofsurfaceconsonantclustertype?
• The hierarchywefound supports the second view;i.e.that twoconsonants areseparated by asyllableboundary.
ʃ_t >>ɸ_s >>k_s
(t)s_t t(s)_t• Affricates can variablybe treatedas anordered
fricative-stop segmental complex (Sagey 1986) orstrident stop (Clements 1999) (cf. Lombardi 1990).
Acaveat• Eachphonologicalenvironmentwastestedwithoneitemonly.
• Afollow-upexperimenthasbeenrunwithanadditional6speakersproducingeachofthebelowdyads10-15times(butthedataisyettobeanalyzed).
FS FF SS SFɸuton~ɸudou(布団—不動)ɸutan~ɸudan(負担—不断)ɸuta~ɸuda(ふたー札)
ɸusoku~ɸuzoku(不足—付属)ɸusai~ɸuzai(負債—不在)ɸusagaru~ɸuzakeruふさがる ふざける
kutakuta~kudaranuくたくた-くだらぬkutabaru~kudasaruくたばる くださるkutaniyaki~kudanshita九谷焼 九段下
kusami~kuzai臭みー句材kusari~kuzawa鎖 久沢kusakari~kuzakicho草刈り 久崎町
ʃutaisei~ ʃudaika(主体性—主題歌)ʃutou~ʃudou(酒盗—手動)ʃutokou~ʃudouken首都高 主導権
ʃusai~ʃuzai(主催ー取材)ʃusa~ʃuzan(主査-珠算)ʃuso~ʃuzou主訴 酒造
Entropyalsovariedacrossitems
Temporal stabilityanalysis
• Cross-linguistic workon the articulatory timing ofconsonant clusters has identified timing differencescorrelated withsyllable structure.
• These differences arereflected inpatterns oftemporal stabilityacross CVXand CCVX sequences(Browman andGoldstein, 2007; Shawetal., 2009;Marin, 2012; Hermes etal.,2013; ShawandGafos,2012).
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Patterns oftemporal alignment
CC
V
… CC
V
…
Heterosyllabic parse(simplexsyllableonsets)
[C.CV] [CCV]SyllableParse
CoordinationTopology
SurfacePattern
V
CC
V
CC
Tatuosyllabic parse(complexsyllableonsets)
On the hypothesis thatthe syllable nucleus is coordinated with thesyllable onset…(Browman and Goldstein, 2000)
Temporalstabilitymetrics
Relative Standard Deviation (RSD)
left center right
.05 .02 .07
Relative Standard Deviation (RSD)
left center right
.12 .07 .04
Following: Browman CP, GoldsteinL(1988) Some Notes onSyllable Structure inArticulatory Phonology.Phonetica 45: 140–155. PMID: 3255974
ʃ ʃ
ʃ ʃ tt
Singletoncontrolwords forstabilityanalysis(alreadyrecorded)
Consonant cluster Singleton control
Entropy = 1.99 (W,K) [mastaa]マスター bataa バター
Entropy = 1.89 (w) [haksai] 白菜 dasai ダサい
Entropy = 1.46 [ʃtaisei]主体性 taisei 体制
Entropy = 1.08 (W,K) [ɸsoku]不足 kasoku 加速
Entropy = 0.09 (W,K) [katstoki]勝つ時 mirutoki 見る時
Methods
Posteriordeletionprobability
Targetabsent
Targetpresent
ʃtai
tai
Bayesian decision rule applied toposterior probabilities
Target absent tokens (n= 138) were compared tosingleton
controls
LE
RECC
AAA
Preliminary results: ʃutaisei
Relative Standard Deviation(RSD)
LE_A CC_A RE_A.23 .18 .11
The right-edge toanchor (RE_A) Interval is the moststable,
an indication of simplex onsets
Data froma totalof 276tokens, 138taisei and 138shutaisei with<.5 probability of voweltarget; NB: data are from5speakers, as one speaker (S05) hadnotargetless /u/ tokens.
Conclusion
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• The articulatory nature ofdevoiced vowelswasbarelyknown(modulo Funatsu &Fujimoto2011).
• We providedfirstsystematic analyses oftherelevantarticulatory data.
• Voweliseither deleted or retained, butnever (oronlyveryrarely) reduced.
• The likelihoodofdeletionvariesacrossdifferentconsonantalenvironments,butsystematically so.
• There isinter-speaker variation aswell.• Notentirely consistentwithKawakami’s(1971)orWhang’s(2014,2016)predictions.
• Notclear effects ofconsonant-conditionedentropy either.
• Weconjectured thatour results support theheterosyllabic analysis of the “resulting clusters”(Matsui 2005).
• Somephonologicalevidence• Syllablecontact effect• Temporal stabilitypatterns
• Butmore needs tobe done, especially toconfirmthatJapanese follows SyllableContact Law(theemergence of theunmarked?).
Acknowledgements
• Research supported by theJSPSgrants (#26770147and #26284059, and especially #15F15715, whichsupported our collaboration).
• Thanks to JeffMoore and Chika Takahashi fortheirhelpwith theexperiment and EMAanalysis.