In this paper, the probability distribution functions (pdf's) of the formant spaces of three major accents of the English language, namely, British Received Pronunciation (RP), General American, and Broad Australian, are modeled and compared. The statistical differences across the formant spaces of these accents are employed for accent conversion. An improved formant tracking method, based on linear prediction (LP) feature analysis and a two-dimensional hidden Markov model (2-D-HMM) of format trajectories, is used for estimation of the formant trajectories of vowels and diphthongs of each accent. Comparative analysis of the formant spaces of the three accents indicates that these accents are partly conveyed by the differences of the formants of vowels. The estimates of the probability distributions of the formants for each accent are used in a speech synthesis system for accent conversion. Accent synthesis, through modification of the acoustic parameters of speech, provides a means of assessing the perceptual contribution of each formant parameter on conveying an accent. The results of perceptual evaluations of accent conversion illustrate that formants play an important role in conveying accents

This paper presents a voice conversion method based on transformation of the characteristic features of a source speaker towards a target. Voice characteristic features are grouped into two main categories: (a) the spectral features at formants and (b) the pitch and intonation patterns. Signal modelling and transformation methods for each group of voice features are outlined. The spectral features at formants are modelled using a set of two-dimensional phoneme-dependent HMM. Subband frequency warping is used for spectrum transformation with the subbands centred on the estimates of the formant trajectories. The F0 contour is used for modelling the pitch and intonation patterns of speech. A PSOLA based method is employed for transformation of pitch, intonation patterns and speaking rate. The experiments present illustrations and perceptual evaluations of the results of transformations of the various voice features.

This paper presents analysis through synthesis of the acoustic correlates of British, Australian and American accents by transforming the correlates individually across the accents. The acoustic correlates of accents are grouped into three main categories: (a) the spectral features at formants, (b) the pitch intonation pattern and (c) duration. The modeling and transformation methods for each group of voice features are outlined. The spectral features at formants are modeled using two-dimensional (2D) phoneme-dependent HMM. Subband frequency warping is used for spectrum transformation where the subbands are centred on estimates of the formant trajectories. The F0 contour is used for modeling the pitch and intonation patterns of speech. A method based on the time domain pitch synchronous overlap and add algorithm (TD-PSOLA) is used for transformation of pitch intonation and duration pattern. Perceptual tests based on mean opinion score (MOS) are conducted to rank the main features of accents. Formants are regarded as the most important features of accents, followed by intonation pattern and duration.

The differences between formants of British, Australian and American English accents are analysed and ranked. An improved formant model based on linear prediction (LP) feature analysis and a two-dimensional(2D) hidden Markov model (HMM) of formants is employed for estimation of the formant frequencies and bandwidths of vowels and diphthongs. Comparative analysis of the formant trajectories, the formant target points and the bandwidth of the spectral resonance at formants of British, Australian and American accents are presented. British vowels and diphthongs have smaller formant bandwidth than Australian. A method for ranking the contribution of different formants in conveying an accent is proposed whereby formants are ranked according to the normalized distances between the formants across accents. The first two formants are considered more sensitive to accents than other formants.

This paper explores methods of estimation and mapping of parametric formant-based models for voice transformation. The main focus is the transformation of the parameters of a model of the vocal tract of a source speaker to a target speaker. The vocal tract parameters are represented with the linear prediction (LP) model coefficients and the associated formant frequencies, bandwidths, intensities and their temporal trajectories. Two methods are explored for vocal tract (formant) mapping. The first method is based on nonuniform frequency warping and the second is based on pole rotation. Both methods transform all parameters of the formants (frequency, bandwidth and intensity). In addition, the factors that affect the selection of the warping ratios for the mapping functions are presented. Experimental evaluation of voice morphing based on parametric models are presented.

This paper explores the estimation and mapping of probability models of formant parameter vectors for voice conversion. The formant parameter vectors consist of the frequency, bandwidth and intensity of resonance at formants. Formant parameters are derived from the coefficients of a linear prediction (LP) model of speech. The formant distributions are modelled with phonemedependent two-dimensional hidden Markov models with state Gaussian mixture densities. The HMMs are subsequently used for re-estimation of the formant trajectories of speech. Two alternative methods are explored for voice morphing. The first is a non-uniform frequency warping method and the second is based on spectral mapping via rotation of the formant vectors of the source towards those of the target. Both methods transform all formant parameters (Frequency, Bandwidth and Intensity). In addition, the factors that affect the selection of the warping ratios for the mapping function are presented. Experimental evaluation of voice morphing examples is presented.

Abstract The differences between the formant trajectories of British and broad Australian English accents are analysed and used for accent conversion. An improved formant model based on linear prediction (LP) feature analysis and a 2-D hidden Markov model (HMM) of formants is employed for estimation of the formant trajectories of vowels and diphthongs. Comparative analysis of the formant values, the formant trajectories and the formant target points of British and broad Australian accents are presented. A method for ranking the contribution of formants to accent identity is proposed whereby formants are ranked according to the normalised distances between formants across accents. The first two formants are considered more sensitive to accents than other formants. Finally a set of experiments on accent conversion is presented to transform the broad Australian accent of a speaker to British Received Pronunciation (RP) accent by formant mapping and prosody modification. Perceptual evaluations of accent conversion results illustrate that besides prosodic correlates such as pitch and duration, formants also play an important role in conveying accents.