Abstract
This paper aims to provide an overview of the emerging area of non-linear predictive modelling for speech processing. Traditional predictors are linear based models related to the speech production model. However, non-linear phenomena involved in the production process justify the use of non-linear models. This paper investigates certain statistical and signal processing perspectives and reviews a number of non-linear models including their structure and key parameters (such as prediction context).
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .
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Chetouani, M., Hussain, A., Faundez-Zanuy, M., Gas, B. (2005). Non-linear Predictive Models for Speech Processing. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_123
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DOI: https://doi.org/10.1007/11550907_123
Publisher Name: Springer, Berlin, Heidelberg
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