Title :
Analysis and Synthesis of Formant Spaces of British, Australian, and American Accents
Author :
Yan, Qin ; Vaseghi, Saeed ; Rentzos, Dimitrios ; Ho, Ching-Hsiang
Author_Institution :
Inst. of Acoust., Acad. Sinica, Beijing
Abstract :
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
Keywords :
hidden Markov models; natural language processing; probability; speech synthesis; American accents; Australian accents; British accents; British received pronunciation; accent conversion; formant spaces synthesis; format trajectories; linear prediction feature analysis; probability distribution functions; speech synthesis system; two-dimensional hidden Markov model; Acoustical engineering; Australia; Hidden Markov models; Humans; Natural languages; Probability distribution; Speech recognition; Speech synthesis; Trajectory; Vocabulary; Formant; hidden Markov model (HMM); linear prediction (LP);
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
DOI :
10.1109/TASL.2006.885923