Analysis, Modelling and Synthesis of

British, Australian and American Accents

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

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

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

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.

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.

(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.

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.

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 ****

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

TrainingLabeling &

Segmentation

Formants

& Trajectories

Pitch Contour

Tracker

Pitch

Marker Tone Nucleus

Features

F0 Range/Mean

Pitch Accents

Accent

Profile

Speaking Rate

& Durations

Input

Speech

Block diagram illustration of the processes involved in accent analysis

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.

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

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

Australian British American

Du

rati

on

(s

ec

)

Model

Input

British

Model

American

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.

Formant Estimation with 2D-HMM

Segmentation

& window

LPC

Model

Polynomial

roots

LP-based Formant-candidate feature extraction method

Formant candidate

Feature vector Speech

Frequency,Bandwidth

Intensity 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

Destimator

LPC

P1 P2 P3 P4 P5 P6

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.

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

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.

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.

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

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)

Accent Morphing Method

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

Source SpeechSpeech Labeling

& SegmentationFormant Mapping

Formant

Estimation

Prosody

Modification

Accent ModelHMM Training/

Adaptation

Accent Synthesised

Speech

• 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

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

SpeechLinear Prediction

ModelLP Spectrum

Mapping

Formant

Estimation

Formant Transformation

Ratios

Accent modified

spectrum

Formant HMMs

Polynomial roots

Pole estimation

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 a

Si

Si

Ti

Ti

iiff

ff

1

1

)1(a

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.

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

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 ‘asked’ transformed to British accent

(a) (b)

(c) (d)

Model

Estimation

LPModel

FormantTrajectory

Source

Speech

Target

Speech

LPModel

FormantTrajectory

Mapped

SpeechWarping Factors

Target

Speaker

HMM

Model

Source

Speaker

HMM

Model

Formant

TrackingFormant Mapping

SpeechRecon

struction

Speech

Reconstruction

Model

Estimation

LPModel

FormantTrajectory

Source

Speech

Target

Speech

LPModel

FormantTrajectory

Mapped

SpeechWarping Factors

Target

Speaker

HMM

Model

Source

Speaker

HMM

Model

Formant

TrackingFormant Mapping

SpeechRecon-

struction

Speech

Reconstruction

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

Accent Conversion Demonstration

Australian British Transformed

British American Transformed

‘Article’

‘Claim’

‘Cooperation’

‘Beige’

Source Accent Target AccentSpoken

word

‘Boston’

‘Opposition’

‘The occupied’

The End