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
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
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 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 .
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 dictionary 2 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 /æ Ɔ / for / au / .
b) Differences in phonetic realizations : phoneme substitution, deletion , insertion.
For example, ‘ JOHN’ is pronounced as / ʤΛ n/ 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 /s æi / 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
F our aspects of acoustic correlates of accents are considered essential for accent models and accent synthesis. These are:
(a) Formant s (i.e. frequency of vocal tract resonance) correlates of accents, including :
( i ) Formant trajectories F k j ( t ), k is the formant index and j is phoneme index .
(ii) Timing and magnitude of the f ormant 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 dip h thongs . (ii) Relative duration and timings of the two constituent vowels of dip h thongs. (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 2 nd 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 F 0 mean Average of pitch * F 0 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 Training Labeling & 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 s peaking 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 Duration (sec)
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.
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.
7.28 27.3 33.1 Australian 29.94 8.8 30.6 American 34.9 29.3 12.8 British Australian Model American Model British Model Model Input Speaking Rate (number/sec) Phone Word British 12.1 3.64 American 11.6 3.1 Australian 10.8 2.8
Formant feature extraction, illustrated consists of three main functions,
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 A k is the pole radius, F i the pole frequency and F s sampling frequency.
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 close r.
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
2 nd Formant has widest frequency rang e and is most sensitive to Accen t
Formant Ranking using a normalised distance Figure : Comparison of formants of Australian, British and American (female) Formant Ranking Order Accent Pairs 4 th 3 rd 1 st 2 nd Australian & American 4 th 3 rd 1 st 2 nd British & American 3 rd 4 th 2 nd 1 st British & Australian 4 3 2 1
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 Model HMM 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
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. F 01 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 F 12 F 23 F 34 F 45 BW 1 BW 2 BW 3 BW 4 I 12 I 23 I 34 Magnitude (dB) 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 roots Pole estimation
The frequency bands of the source speaker [ F 01 F 12 F 23 F 34 F 45 ] 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 ( i i i i i i f f S i S i T i T i i i f f f f 1 1 ) 1 ( Where f i T and f i S are the i th 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 ‘article’ transformed to British accent (a) (b) (c) (d)
Model Estimation LP Model Formant Trajectory Source Speech Target Speech LP Model Formant Trajectory Mapped Speech Warping Factors Target Speaker HMM Model Source Speaker HMM Model Formant Tracking Formant Mapping Speech Recon struction Speech Reconstruction LPC - Spectrum Warping / Pole Rotation Model Estimation LP Model Formant Trajectory Source Speech Target Speech LP Model Formant Trajectory Mapped Speech Warping Factors Target Speaker HMM Model Source Speaker HMM Model Formant Tracking Formant Mapping Speech Recon - struction Speech Reconstruction LPC - Spectrum Warping / Pole Rotation 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 Accent Spoken word ‘ Boston’ ‘ Opposition’ ‘ The occupied’