Fujisaki Model 對應階層性語流韻律架構 HPG 在國語的應用與分析

Fujisaki ModelHPG

[email protected]

OutlineHierarchical Framework of Discourse Prosody HPGIntroductionThe HPG frameworkProsodic features and templates of Mandarin fluent speech prosodyCorpus approach and quantitative evidences

Fujisaki Model(F0 model)Auto-extraction Phrase componentsAccent components

Predicting cross-phrase F0 patterns with higher level discourse information using the Fujisaki model

Experiment & results

Conclusion

Reference Tseng, Chiu-yu (2006). Prosody Analysis,in Advances in Chinese Spoken Language Processing, edited by Chin-Hui Lee, Haizhou Li, Lin-shan Lee, Ren-Hua Wang, Qiang Huo, World Scientific Publishing, Singapore,pp.57-76. Tseng Chiu-yu, Pin Shao-huang, Lee Yeh-lin, Wang Hsin-min and Chen Yong-cheng (2005). Fluent speech prosody: framework and modeling, Speech Communication, Vol.46,issues 3-4,(July 2005), Special Issue on Quantitative Prosody Modelling for Natural Speech Description and Generation, pp.284-309.Fujisaki H, Hirose K. Analysis of voice fundamentalfrequency contours for declarative sentences ofJapanese. J.Acoust. Soc.Jpn.(E), 1984; 5(4): 233-242.Mixdorff, H. (2000): A Novel Approach to the Fully Automatic Extraction of Fujisaki Model Parameters. Proceedings of ICASSP 2000, vol. 3, pages 1281-1284, Istanbul, Turkey. Mixdorff, H., Hu, Y. and Chen, G. (2003): Towards the Automatic Extraction of Fujisaki Model Parameters for Mandarin. In Proceedings of Eurospeech 2003, Geneva. Wentao Gu, Hirose K, Fujisaki H: Comparison of Perceived Prosodic Boundaries and Global Characteristics of Voice Fundamental Frequency Contours in Mandarin Speech. ISCSLP 2006: 31-42

HPG (Hierarchical Prosodic Phrase Grouping) Framework of Discourse Prosody--Fluent Speech Prosody

Introduction of HPG (1/2)From bottom up, output fluent speech prosody includes lexical prosody (tone), syntactic prosody (intonation) and discourse prosody (cross-phrase semantic associations).

From top down, the HPG framework represents hierarchical constraints discourse, syntactic and lexical information. Thus, higher level prosodic units constrain and govern lower level ones; lower level units are subject to and associated by higher level units.

Phrases in speech flow should NOT be treated as independent, unrelated prosodic units. Rather, intonation units are subordinate prosodic units subject to HPG specifications.

Introduction of HPG (2/2)4. Output fluent speech prosody results from cumulative layered contributions from lexical, syntactic and discourse information. Therefore, prosody does NOT stop at phrase intonation.

5. According to HPG specifications, variations of phrase intonations across speech flow are systematic and predictable.

HPG (Hierarchical Prosodic Phrase Grouping)--Discourse Prosody Hierarchy(unit and constraints)

A schematic representation of how PGs form spoken discourse

Speech data annotationThe speech data were manually labeled by independent transcribers for perceived boundaries and breaks (pauses), using a 5-step break labeling system corresponding our framework.

Hand Labeling Perceived Boundary (Tseng et al, 1999) in Relation to Prosody Organization Systematic and Predictable

COSPRO http://www.myet.com/corporaFlow chart of speech data processing and annotation-Read speech Task flow output files and file names footnotes Recording Speechin Sound Proof ChambersHand Mapping RecordedSpeech with TextSegmenting Speech Filesusing HTKSpot-checking by HandHand-labeling PerceivedProsodic BoundariesAnalyzing LabeledSpeech Data*.wavEditing Text to MatchSpeech Files*.phn*.adjust*.breakPG modelConverting Text to SAMPA*.SAMPAText for speakers to readDesigning Text for Narrationfile extension: *.textSerial numbers for text and wav files are identical. sampling rate: 16000Hzsampling format: 1 channel 16-bit linearHand Correcting MismatchFile extension: *.adjustAdjustments:segment boundariesmultiple pronunciation characters

Cross-Phrase Prosodic Features and TemplatesCorpus investigations and quantitative analyses enabled us to

1. obtain quantitative evidences of cumulative contributions of prosodic layers to output prosody,

2. derive cross-phrase hierarchical templates corresponding to every prosodic layer in the following 4 acoustic correlates (Tseng et al, 2004; 2005; 2006)

1. F0 contour templates2. Duration cadence templates3. Intensity distribution patterns4. Pause cadence templates

Quantitative Analysis and Predictions: F0, Duration , Intensity and BreaksHierarchical linear modelFujisaki parametersPauseDurationIntensity

Auto-Extraction for Fujisaki ModelFujisaki parametersF0 contour

The Fujisaki Model

Fujisaki Model (1984)Intonation modelUnitsyntax defined simple sentence

F0 curve corresponding to single simple phrase as defined by syntax can be generated

Generation of gradually declining baselines of F0 curve can be decomposed into the phrase components (Ap) and accent components (Aa)

Evidences obtained: Japanese, English, German, Mandarin, Thai, Vietnameseetc.

The Fujisaki Model (1/2)F0=Base frequency+ Phrase components+ Accent components

The Fujisaki Model (2/2)

Phrase components= 0.01~0.05

Accent components= 0.1~0.5

Simulation of Mandarin Prosody with Fujisaki ModelPhrasecomponentsAccentcomponentsSimulated ResultApAaFb

Simulating/Generating F0 Curves with Fujisaki ModelAuto-extraction of Parameters

(other approaches vs. our approach)

Mixdorff (2000, 2003)-- Interpolation and Smoothing (1/3)Intermediate F0 values for unvoiced speech segments Microprosodic variations are smoothed out. Feature: very close simulation, one phrase at a time.

Mixdorff (2000, 2003)High-Pass Filtering and Component Separation (2/3)highpass filter(stop frequency at 0.5 Hz)The output of the highpass filter(HFC)low frequency contour (LFC): containing the sum of phrase component and Fb.

Component SeparationFb : the overall minimum of the LFC Phrase components : the residual of LFC subtracted Fb

Mixdorff (2000, 2003)-- Optimizing simulated F0 curve (3/3)Hill-Climbing MethodologyConstruct a sub-optimal solution that meets the constraints of the problem Take the solution and make an improvement upon it Repeatedly improve the solution until no more improvements are necessary/possible

Gu (2006 Generating F0 Curves Using Speech Sample from CORSPRO_051.Gu did NOT consider information above phrases.2.Gu compared generation results with HPG labeled results.

Gu (2006)Simulation of F0 Curves w/out Higher Level and Boundary InformationFeatures:Local minimum of LFC are considered and inserted with ApF0 curves and boundaries are generated

Gu (2006) observed large variations of Aps exist1. between two speakers, 2. among boundaries We observed: 1. The magnitude of Ap inserted in larger boundaries (B4, B5) are similar.2. Similar patterns exist in BGs or PGs.

Why Higher Level Discourse Information? (1/2)Gu (2006)s traditional approach without higher level information

Focus: 1. Isolated phrase intonations and boundaries are generated one at a time. 2. Simulation and fine tuning of each generation. Problems: 1. Large variations of Aps exist between speakers and among boundaries.2. Variations can not be predicted and/or solved; concatenation of each generation can not yield patterns for technological implementation.

Why Higher Level Discourse Information? (2/2)Tseng et al approach with higher level discourse information (HPG)

Focus:Prediction of fluent speech prosody, i.e., cross-phrase F0 curves and boundary break

Advantages: 1.Multiple phrase intonations and boundaries can be predicted according to HPG specifications.2. Output prosody is NOT concatenation of independent isolated phrase intonations.3. Between-speaker and among-boundary Ap variations are systematic and predictable, therefore, are NOT considered variations by HPG framework.4. Useful to technology development (speech synthesis).

2 ExperimentsHypothesis Predictions of phrase intonation curves can be improved with higher level information because HPG specifies cross-phrase associations.Cumulative contributions from prosodic layers can provide useful information.

Implicationstechnology development

Speech DataSinica COSPRO 08

Carrier paragraph: A 30-syllable, 3-phrase complex sentence representing a short PG was constructedA target single syllables was embedded in three PG positions, i.e., PG-Initial, -medial and final.

Speaking rates:289 and 308 ms/syllable for M054C and F054C

Target syllable analyzed:Tone 1

Goals:1. Patterns of Ap could be derived from speech data.

2. Evidence of interaction between phrase command and higher-level prosodic units could be found.

3. Evidences found could predict cross-phrase F0 allocation in speech flow. Experiment 1

Distribution of speech dataRange of values of Ap from phrases produced by female speaker F054cin three PG related positions are presented.

PG PositionAp range-Initial0.959~0.499-Medial0.615~0.04-Final0.678~0.093

Distribution of speech dataA schematic representation of the distribution of Ap of F054c where the horizontal axis represents values of Ap and the vertical axis represents number of Ap occurrence.

ResultsThe expected cell mean of predictions with and without the PG effect. The Figure is a schematic representation of the patterns of phrasesafter PG effect is taken into consideration.

Expected Cell Mean at the PPh levelwithout PG effects:0.4595Expected Cell Mean at the PG levelwith PG effect:PG InitialPG MedialPG Final0.69840.35360.3265

ExamplesOne expected cell mean cant approach LFC well, PG-initial and PG-final especially. without PG-effectwith PG-effect

Superimposed F0 according to the HPG Framework SylPPhPGF0F0F0ttt

What Does Higher Level Discourse Information Mean? Swapping PG-initial and PG-finalF0tF0ExchangedOriginalt

Further Evidences of HPG, Systematic and PredictableSame Base Form and Different Distribution Yield Different Output Prosody Styles

Speech DataMandarin rhymed classical writing

Styleregularsemi-regularirregularWeatherBroadcast

Styleirregular

# of Syl# of PPh# of Discoursespeech_rate(ms)female f054705472034193female m054709674734165

# of Syl# of PPh# of Discoursespeech_rate(ms)female f054350271030271female m056351071130202

Classification of Stylistic Variationsregularirregularsemi-regular

IndexName of files # of syllablesstyle of writing07a30017a9018a8019a15021a5022a12023a4024a16026a5027a262

IndexName of files # of syllablesstyle of writing01a10702a18703a20206a150

IndexName of files # of syllablesstyle of writing07a30017a9018a8019a15021a5022a12023a4024a16026a5027a262

Predictions of Ap from Higher Level information (B3, B4, B5)PPhBGPG

Distributions of Layered Contributions in Each Style (Male)Rhymed classical writing m056 regular semi-regular irregularWeather broadcast m054 (irregular)The more regular the style, the bigger the planning templates, and the more governing from higher level information

Chart28

0.4471312388

0.1758515012

0.0028635669

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR

AnalysisofVarianceForApAnalysisofVarianceForApAnalysisofVarianceForAp

NoSelectorNoSelectorNoSelector

SourcedfSumsofSquaresMeanSquareF-ratioSourcedfSumsofSquaresMeanSquareF-ratioProbSourcedfSumsofSquaresMeanSquareF-ratioProb

Const137.416737.4167584.5?0.0001Const167.222467.2224988.01?0.0001Const128.007228.0072429.47?0.0001

PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694

Error825.249210.0640147Error17812.11090.0680385Error362.347670.0652131

Total908.06578Total23421.9368Total896.55283

0.34919995340.44791856610.6417318929

ANOVA

AnalysisofVarianceForresiduals(LM)AnalysisofVarianceForresiduals(LM)AnalysisofVarianceForresiduals(LM)


F-ratioProb

SourcedfSumsofSquaresMeanSquareF-ratioSourcedfSumsofSquaresMeanSquareF-ratioProbSourcedfSumsofSquaresMeanSquare

Const18.45E-318.45E-313.02E-291Const15.04E-325.04E-321.20E-301Const14.93E-314.93E-312.26E-291

BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044

FrPPhBGPGmrPPhBGPGirPPhBGPG

Error5.249212.125772.00892Error12.11099.211239.14679Error2.347671.502421.43479

Total8.065785.249212.12577Total21.936812.11099.21123Total6.552832.347671.50242

Contribution0.34919995340.38724587080.0144871296Contribution0.44791856610.13218290730.0029375296Contribution0.64173189290.12899006990.0103207317

M&F

FrmrirPPhrmrirAverage

PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317

Total0.75093295380.5830390030.78104269450.7050048838BGrmrirAverage

F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175

BG0.17585150120.13130555430.0707157574PGrmrirAverage

PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf

AnalysisofVarianceForApAnalysisofVarianceForresiduals(LM)AnalysisofVarianceForresiduals(LM)


SourcedfSumsofSquaresMeanSquareF-ratioProbSourcedfSumsofSquaresMeanSquareF-ratioProbSourcedfSumsofSquaresMeanSquareF-ratioProb

Const1218.992218.9924869.3?0.0001Const14.74E-294.74E-292.06E-271Const18.39E-328.39E-323.71E-301

PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F

FrmrirWBPPhrmrirWBAverage

PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838

MrmrirWBBGrmrirWBAverage

PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.4471312388

BG0.1758515012

PG0.0028635669

Sheet3

regular

Chart30

0.7324688175

0.0707157574

0.0099063487

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR





PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694



0.34919995340.44791856610.6417318929

ANOVA



F-ratioProb



BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044





M&F


PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317


F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175


PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf





PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F


PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838


PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.7324688175

BG0.0707157574

PG0.0099063487

Sheet3

regular

Chart31

0.6032509753

0.0372496749

0.0207845687

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR





PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694



0.34919995340.44791856610.6417318929

ANOVA



F-ratioProb



BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044





M&F


PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317


F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175


PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf





PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F


PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838


PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.6032509753

BG0.0372496749

PG0.0207845687

Sheet3

regular

Chart37

0.5036367355

0.1313055543

0.0089268341

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR





PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694



0.34919995340.44791856610.6417318929

ANOVA



F-ratioProb



BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044





M&F


PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317


F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175


PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf





PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F


PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838


PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.5036367355

BG0.1313055543

PG0.0089268341

Sheet3

regular

Distributions of Layered Contributions in Each Style (Female)Rhymed classical writing f054 regular semi-regular irregularWeather broadcast f054(irregular)The more regular the style, the bigger the planning templates, and the more governing from higher level information

Chart32

0.3491999534

0.3872458708

0.0144871296

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR





PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694



0.34919995340.44791856610.6417318929

ANOVA



F-ratioProb



BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044





M&F


PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317


F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175


PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf





PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F


PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838


PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.3491999534

BG0.3872458708

PG0.0144871296

Sheet3

regular

Chart34

0.4479185661

0.1321829073

0.0029375296

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR





PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694



0.34919995340.44791856610.6417318929

ANOVA



F-ratioProb



BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044





M&F


PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317


F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175


PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf





PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F


PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838


PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.4479185661

BG0.1321829073

PG0.0029375296

Sheet3

regular

Chart35

0.6417318929

0.1289900699

0.0103207317

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR





PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694



0.34919995340.44791856610.6417318929

ANOVA



F-ratioProb



BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044





M&F


PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317


F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175


PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf





PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F


PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838


PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.6417318929

BG0.1289900699

PG0.0103207317

Sheet3

regular

Chart36

0.6276715591

0.0500214486

0.0023423124

regular

Sheet1

1.100810.49696B4B5

0.784610.482151.100811.23486

1.007870.343660.784611.25293

0.798260.518461.007870.8624

1.234860.735860.798260.93157

0.76610.511620.76611.1001

0.73030.236580.73031.076372

1.024750.551161.024751.23486

0.930460.57750.930461.25293

0.925370.51560.925370.8624

1.002020.410571.002020.93157

1.252930.694180.726961.1001

0.726960.621740.838760.1572296584

0.838760.538181.00134

0.86240.619990.91702

1.001340.673760.91854

0.917020.286060.8447

0.918540.570731.13446

0.931570.413070.83847

0.844700.58703

1.134460.538670.8883068421

0.838470.601280.1360456822

1.10010.54867

0.587030.663960.88830684210.9997768049

0.16355643620.1634009246

0.92748708330.5062670833

Sheet2

Sheet3

RIR





PPh82.816580.3520725.4999?0.0001PPh569.825920.1754632.5789?0.0001PPh534.205160.07934261.21670.2694



0.34919995340.44791856610.6417318929

ANOVA



F-ratioProb



BG143.123440.2231037.9763?0.0001BG142.899620.2071164.9467?0.0001BG208.45E-014.23E-021.94E+000.0225



0.59503049030.23942646710.3600378247





P_F20.1168520.05842622.55930.0831P_F20.06443580.03221790.817180.4429P_F20.06762520.03381262.05030.1349



0.05496831740.00699580840.045014044





M&F


PPh0.34919995340.44791856610.6417318929F0.34919995340.44791856610.64173189290.4796168041

BG0.38724587080.13218290730.1289900699M0.44713123880.50363673550.73246881750.5610789306

PG0.01448712960.00293752960.0103207317


F0.38724587080.13218290730.12899006990.216139616

MrmrirM0.17585150120.13130555430.07071575740.1259576043

PPh0.44713123880.50363673550.7324688175


PG0.00286356690.00892683410.0099063487F0.01448712960.00293752960.01032073170.0092484636

Total0.62584630680.6438691240.81309092360.6942687848M0.00286356690.00892683410.00990634870.0072322499

WBf





PPh30631.31240.1023282.2753?0.0001pib192.495450.1313395.7179?0.0001ppg330.5826840.01765710.781660.8061



rPPhBGPG

Error18.574216.07882.00892

Total49.886618.57422.12577

Contribution0.62767155910.05002144860.0023423124

WBM





PPh30127.83410.09247192.2479?0.0001pib191.718670.09045623.9646?0.0001ppg380.9590440.0252381.14330.2579



rPPhBGPG

Error18.30616.587315.6283

Total46.1418.30616.5873

Contribution0.60325097530.03724967490.0207845687

M&F


PPh0.34919995340.44791856610.64173189290.6276715591female0.34919995340.44791856610.64173189290.62767155910.4796168041

BG0.38724587080.13218290730.12899006990.0500214486male0.44713123880.50363673550.73246881750.60325097530.5610789306

PG0.01448712960.00293752960.01032073170.0023423124

Total0.75093295380.5830390030.78104269450.7050048838


PPh0.44713123880.50363673550.73246881750.6032509753female0.38724587080.13218290730.12899006990.05002144860.216139616

BG0.17585150120.13130555430.07071575740.0372496749male0.17585150120.13130555430.07071575740.03724967490.1259576043

PG0.00286356690.00892683410.00990634870.0207845687

Total0.62584630680.6438691240.81309092360.6942687848

PGrmrirWBAverage

female0.01448712960.00293752960.01032073170.00234231240.0092484636

male0.00286356690.00892683410.00990634870.02078456870.0072322499

Mregular

PPh0.6276715591

BG0.0500214486

PG0.0023423124

Sheet3

regular

PPh Contributions in Different Styles

PPhrsmrirrWBfemale0.34920.4479190.6417320.627672male0.44713120.5036370.7324690.603251

Chart2

0.34920.4471312

0.4479190.503637

0.6417320.732469

female

male

Sheet1

PPhrsmrirr

female0.34920.4479190.641732

male0.44713120.5036370.732469

Sheet1

female

male

Sheet2

Sheet3

Contributions of BG Layer in Different Styles

BGrsmrirrWBfemale0.38724590.1321830.128990.050021male0.17585150.1313060.0707160.03725

Chart3

0.38724590.1758515

0.1321830.131306

0.128990.070716

female

male

Sheet1

BGrsmrirr

female0.38724590.1321830.12899

male0.17585150.1313060.070716

Sheet1

female

male

Sheet2

Sheet3

Conclusions

1. Lexical, syntactic and discourse prosody ALL contribute to output prosody. Interactions are necessary, systematic and predictable from higher level considerations.HPG accounts for prosody of fluent continuous speech.

2. How a semantic complete speech paragraph begins, holds and ends across the phrases within is specified by HPG related positions:PG-Initial, PG-Medial and PG-final

3. Further evidences from Mandarin rhymed classics substantiated HPG as a base form for both planning and processing of fluent speech prosody.

4. Stylistic variations are built on the same base form with varied contribution distribution.

Documents

Fujisaki Model 對應階層性語流韻律架構 HPG 在國語的應用與分析