DocumentCode
417226
Title
Analysis by synthesis of acoustic correlates of British, Australian and American accents
Author
Yan, Qin ; Vaseghi, Saeed ; Rentzos, Dimitrios ; Ho, Ching-Hsiang
Author_Institution
Dept. of Electron. & Comput. Eng., Brunel Univ., Uxbridge, UK
Volume
1
fYear
2004
fDate
17-21 May 2004
Abstract
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.
Keywords
acoustic correlation; feature extraction; frequency estimation; hidden Markov models; spectral analysis; speech processing; speech recognition; speech synthesis; 2D phoneme-dependent HMM; American accent; Australian accent; British accent; F0 contour; MOS; TD-PSOLA; acoustic correlates; analysis by synthesis; duration; formant spectral features; formant trajectory estimates; mean opinion score; modeling methods; perceptual tests; pitch intonation pattern; spectrum transformation; subband frequency warping; time domain pitch synchronous overlap and add algorithm; transformation methods; two-dimensional HMM; voice features; Australia; Automatic speech recognition; Frequency estimation; Hidden Markov models; Loudspeakers; Natural languages; Spatial databases; Speech analysis; Speech synthesis; Tongue;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-8484-9
Type
conf
DOI
10.1109/ICASSP.2004.1326066
Filename
1326066
Link To Document