Download - Accent seminar

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Analysis, Modelling and Synthesis of

British, Australian and American Accents

Qin Yan Saeed Vaseghi

Multimedia Communication Signal processing Lab

Department of Electronic and Computer Engineering

Brunel University

Supported by EPSRC

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Content

1- Introduction to Phonetics and Acoustics of Accents

2- Research Issues in Modelling Acoustics of Accents of English

3- Current Research Problems

4- Accent Analysis and Models

5- Accent Morphing

6- Audio Demo

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1.1 Background

• Accents are acoustic manifestations of differences in pronunciation and intonations by a community of people from a national, regional or a socio-economic grouping.

• Accents are dynamic processes in that they evolve over time influenced by large-scale immigration, socio-economic changes and cultural trends.

• Applications of accent models include:

- speech recognition,

- text to speech synthesis,

- voice editing,

- accent morphing in broadcasting and films,

- toys and computer games,

- accent coaching, education.

1. Introduction to Phonetics and Acoustics of Accents

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• The importance of an accent feature depends on its distance from that of the ‘standard’ or ‘received’ pronunciation and the frequency with which that feature occurs in the acoustics of speech.

1.2 Basic Structure of Accents

• Generally the structural differences between accents can be divided into two broad parts:

(a) Differences in phonetic transcriptions.

(b) Differences in acoustics correlates and intonations of accents.

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1.3 Phonetics of Accents

• A dominant aspect of accents is in the differences in pronunciation as transcribed by a phonetic dictionary.

• The differences in phonetic transcription can be categorized into two classes:

a) Differences in the number and identity of the phonemes. For example, British English as transcribed by Cambridge University’s BEEP

dictionary2 has five extra vowels: /ax(ə) ea(ɛə) ia(iə) ua (uə) ah (ɒ) / compared to American as transcribed by Carnegie Melon University CMU dictionary. /iə ɛə uə/,are allophones of /i ɛ u/. American /ɒ/ is merged with /a/ compared with British accent.

American transcription has three different levels of stress for vowels and diphthongs. Also Australian English has distinctive vowels such as /æi/ instead of /ei/ and /æƆ/for /au/.

b) Differences in phonetic realizations: phoneme substitution, deletion, insertion.

For example, ‘JOHN’ is pronounced as /ʤΛn/ in American but as /ʤƆn/ in British and Australian English. The word ‘SAY’ is pronounced as /sei/ in British and American but it is pronounced as /sæi / in Australian.

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1.4 Acoustics of Accents

• Perceived acoustics differences of accents are due to the differences, during the production of sound, in the configurations, positioning, tension and movement of laryngeal and supra-laryngeal articulatory parameters, namely vocal folds, vocal tract, tongue and lips

• Four aspects of acoustic correlates of accents are considered essential for accent models and accent synthesis. These are:

(a) Formants (i.e. frequency of vocal tract resonance) correlates of accents, including:

(i) Formant trajectories Fkj(t), k is the formant index and j is phoneme index.

(ii) Timing and magnitude of the formant target point(s) in formant space for each phonetic unit.

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(b) Pitch prosody correlates of accents, include:

(i) Pitch trajectory at various linguistic contexts and positions. e.g. pitch rise, at the beginning of a voiced group or phrase, pitch fall at the end of a phrase.

(ii) Pitch nucleus i.e. the timing and magnitude of the prominent pitch event in a voiced group.

(c) Duration and Timing correlates of accents,

(i) Duration of vowels and diphthongs.

(ii) Relative duration and timings of the two constituent vowels of diphthongs.

(d) Laryngeal (glottal) correlates of accents, i.e the voice quality of speech segments in certain contexts as a function of accent.

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2. Research Issues in Modelling Acoustics of Accents of English

• Definition of an accent ‘feature set’ composed of formants’ trajectories, formants’ target points, pitch trajectory, power trajectory, duration.

• Separation, normalisation, or averaging out of speakers’ characteristics from accent characteristics, this is required for modelling parameters of accent.

• Modelling formants of vowels and diphthongs, the latter is composed of two connected elementary sounds.

• Modelling the duration of vowels and diphthongs and the relative duration of the two halves of diphthongs.

• Modelling pitch trajectory in different phonetic/linguistic positions and contexts.

• Modelling voice quality correlates of an accents in different phonetic/linguistic positions and contexts.

• Integration of all accent features within a coherent generative model.

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Accent Profile (AP)

Parameters Comments Rank

Phonetic Parameters

Substitution, insertion, deletion

Pronunciation differences obtained from phonetic transcription dictionaries

*****

Supra-laryngeal and Laryngeal Correlates

Formants & their trajectories 2nd formant with largest variance is most sensitive to accent ****

Glottal pulse (Voice Quality) Durations and shapes of opening and closing of glottal folds **

Prosody Correlates

F0 mean Average of pitch *

F0 range Range of pitch *

Pitch Nucleus Prominent point (stressed) within an intonation group (Tone Unit)

***

Initial Pitch Rise First pitch slope of a narrative utterance ***

Final Pitch Lowering Final fall pitch slope of a narrative utterance ***

Final Pitch Rise Final rise pitch slope of a narrative utterance ***

Timing and Delivery Correlates

Speaking Rate Phonemes or words per second *

Phoneme Duration Vowel duration elongation and complete pronunciation all affect

***

Excessive Co-articulation Clipped or short duration sounds ****

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Speech Accent Feature Analysis Method

The basic processes involved in accent analysis includes

• Speech phonetic labelling and boundary segmentation using HMMs

• Pitch trajectory and pitch nucleus estimation

• Formant models and formant track estimation

• Duration and power trajectory analysis

HMM Training

Labeling &Segmentation

Formants& Trajectories

Pitch ContourTracker

Pitch Marker Tone Nucleus

Features

F0 Range/MeanPitch Accents

AccentProfile

Speaking Rate& Durations

InputSpeech

Block diagram illustration of the processes involved in accent analysis

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Analysis of Duration Correlate of AU, US and UK Accent Speech

Figure: Comparison of speaking rates of British, Australian and American.

Figure: Comparison of phoneme durations of British, Australian and American.

0.020.040.060.08

0.10.120.140.160.180.2

aa ae ah ao aw ay eh er ey ih iy ow oy uh uw

Australian British American

Du

rati

on

(se

c)

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Model

Input

British

ModelAmerican

Model

Australian

Model

British 12.8 29.3 34.9

American 30.6 8.8 29.94

Australian 33.1 27.3 7.28

Table : (%) word error of speech recognition across British, American and Australian accents.

• Australian speaking (word) rate is 23% slower than British• American speaking (word) rate is 15% slower than British

Comparison of speaking rates of British, American and Australian Accents.

Speaking Rate (number/sec)

Phone

Word

British 12.1 3.64

American 11.6 3.1

Australian 10.8 2.8

• There is an apparent correlation between automatic speech recognition and speaking rate.

•Australian with the slowest speaking rate obtains the best recognition results followed by American and British.

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Formant Estimation with 2D-HMM

Segmentation & window

LPCModel

Polynomialroots

LP-based Formant-candidate feature extraction method

Formant candidateFeature vector

SpeechFrequency,BandwidthIntensity Calculation

Formant feature extraction, illustrated consists of three main functions, (1) an LP model, (2) a polynomial root finder, and (3) a contour trend estimator.

Consider the z-transfer function of an LP model with K real poles and I complex pole pairs and a gain factor G as

where Ak is the pole radius, Fi the pole frequency and Fs sampling frequency.

I

isFiFπj

isFiFπj

i

K

k k zeAzeAzAGzH

11)/(21)/(2

11 )1)(1(

1

)1(

1

estimator

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L P C

P 1 P 2 P 3 P 4 P 5 P 6

Frequency(Hz)

Time(s)

Illustration of of LP spectrum and the modelling of 6 complex pole pairs of a speech segment with an HMM composed of 4 formant-states.

• 2D HMMs span time and frequency dimensions

• Left-right HMM states across frequency model formants such that the first state models the first formant, the second state the second formant and so on

• The distribution of formants in each state is modelled by a mixture Gaussian density.

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Three spectrogram examples of formant tracks superimposed on LPC spectrum of speech

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Comparison of histograms (thin solid line) and Gaussian HMMs of formants of Australian English (bold dashed line). X axis: frequency (Hz); Y axis: probability.

The figures show that HMMS are excellent models of the distribution of the formants.

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Comparison of Formants Spaces of American, Australian and British Accents

Note the following features:

• Rising of vowels /ae/ and /eh/ in Australian.

• Fronting of the open vowel /aa/ and high vowel /uw/ in Australian.

• Fronting and rising of the vowel /er/ in Australian.

• The vowels /iy/, /eh/ and /ae/ in Australian are closer.

F1 vs F2 space of British, Australian and American English. Click phoneme to listen.

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Figure : Comparison of trajectories and target time of formant of British, Australian and American accents

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200

300

400

500

600

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800

900

1000

AA AE AH AO EH ER IH IY OH UW UH

Australian British American600800

1000120014001600180020002200240026002800



2550262527002775285029253000307531503225


Australian British American 350036003700380039004000410042004300440045004600



Accent Pairs

Formant Ranking Order

1 2 3 4

British & Australian 1st 2nd 4th 3rd

British & American 2nd 1st 3rd 4th

Australian & American 2nd 1st 3rd 4th

2

1 )(5.0

V

vBvi

Avi

Bvi

Avi

i FF

FFRank

• 2nd Formant has widest frequency range and is most sensitive to Accent

Formant Ranking using a normalised distance

Figure : Comparison of formants of Australian, British and American (female)

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Accent Morphing Method

Figure : Diagram of a voice morphing system used for accent conversion

Source Speech Speech Labeling & Segmentation Formant Mapping

Formant Estimation

Prosody Modification

Accent ModelHMM Training/Adaptation

Accent SynthesisedSpeech

• Formant Mapping : Transformation of formants of the source towards those of the target accent is based on non-uniform linear prediction model frequency warping.

• Prosody Modification : based on time domain pitch synchronous overlap and add (TD-PSOLA) method.

• Prosody Modification includes pitch slope, duration and power trajectory.

• Application : Text to speech synthesis, Broadcasting System e.g. Accent modification in films, Education software such language teaching, Speech interface in mobile, Call centre and other electronic products

Pitch Tracker

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Formant Transformation via Non-Uniform LP Frequency Warping

Figure Illustration of a non-uniform frequency warping using LP model frequency response. The spectrum is divided into a number of bands centered on the formants and a different set of warping parameters is applied to each band.

F01

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-75

-70

-65

-60

-55

-50

-45

-40

-35

F12 F23 F34 F45

BW1 BW2 BW 3 BW 4

I12

I23 I34

Ma

gn

itu

de

(d

B)

Frequency (Hz)

Figure : Illustration modification of spectrum towards formants of target accent

Speech Linear Prediction Model

LP Spectrum Mapping

Formant Estimation

Formant Transformation Ratios

Accent modified spectrum

Formant HMMs

Polynomial rootsPole estimation

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The frequency bands of the source speaker [F01F12F23F34F45] are mapped to the target accent using a set of warping ratios derived from differences in the formants of phonetic segments of speech across accents as

)1()1()1( iiiiii ff

Si

Si

Ti

Ti

ii ff

ff

1

1

)1(

Where fiT and fi

S are the ith formants of the source and target accents

The frequency mapping can be expressed as

Figure : Illustration of warped(solid line) and original(dash dot line) formant trajectories of /aa/ in accent conversion from Australian to British.

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Pitch Modification Using Time Domain PSOLA (TD-PSOLA)

Source pitch marks

Target pitch marks

• TD-PSOLA is applied into each corresponding voiced speech segment to modify the pitch slope and duration of the segments

Source Speech Pitch Marks

Target Speech Pitch Marks

Illustration of mapping of pitch periods of a source speech to a target

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Examples of changes in accent/duration modulation of pitch

(a) ‘article’ in Australian, (b) Australian-accent ‘article’ transformed to British accent

(c) ‘asked’ in Australian, (d) Australian-accent ‘article’ transformed to British accent

(a) (b)

(c) (d)

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Model Estimation

LPModel

FormantTrajectory

Source Speech

TargetSpeech

LPModel

FormantTrajectory

Mapped SpeechWarping

FactorsTarget

SpeakerHMMModel

Source SpeakerHMMModel

Formant Tracking

Formant Mapping

SpeechRecon

struction

Speech Reconstruction

LPC

- Sp

ect

rum

Warp

ing

/ P

ole

Rota

tion

Model Estimation

LPModel

FormantTrajectory

Source Speech

TargetSpeech

LPModel

FormantTrajectory

Mapped SpeechWarping

FactorsTarget

SpeakerHMMModel

Source SpeakerHMMModel

Formant Tracking

Formant Mapping

SpeechRecon-

struction

Speech Reconstruction

LPC

-S

pect

rum

Warp

ing

/ P

ole

Rota

tion

Transformed(AM m->f)American male American female

An Outline of Voice-Morph: A system for Voice and Accent Conversion

An example of voice

conversion

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Accent Conversion Demonstration

Australian British Transformed

British American Transformed

‘Article’

‘Claim’

‘Cooperation’

‘Beige’

Source Accent Target AccentSpokenword

‘Boston’

‘Opposition’

‘The occupied’

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The End

Download - Accent seminar

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