Doppler-variant modeling of the vocal tract
Author
Summary, in English
A common technique to deploy linear prediction to non- stationary signals is time segmentation and local analysis. Variations of a process within such a segment cause inac- curacies. In this paper, we model the temporal changes of linear prediction coefficients (LPCs) as a Fourier series. We obtain a compact description of the vocal tract model limited by the predictor order and the maximum Doppler frequency. Filter stability is guaranteed by all-pass filtering, deploying the human ear’s insensitivity to absolute phase. The period- icity constraint induced by the Fourier series is counteracted by oversampling in the Doppler domain. With this approach, the number of coefficients required for the vocal tract model- ing is significantly reduced compared to a LPC system with block-wise adaptation while exceeding its prediction gain.
As a by-product it is found that the Doppler frequency of the vocal tract is in the order of 10 Hz. A generalization of the algorithm to an auto-regressive moving average model with time-correlated filter coefficients is straight forward.
As a by-product it is found that the Doppler frequency of the vocal tract is in the order of 10 Hz. A generalization of the algorithm to an auto-regressive moving average model with time-correlated filter coefficients is straight forward.
Publishing year
2008
Language
English
Pages
4197-4200
Publication/Series
ITG Conference on Voice Communication [8. ITG-Fachtagung]
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Document type
Conference paper
Topic
- Electrical Engineering, Electronic Engineering, Information Engineering
Conference name
International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Conference date
2008-03-31 - 2008-04-04
Status
Published
ISBN/ISSN/Other
- ISSN: 1520-6149
- ISBN: 978-1-4244-1483-3