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Nonlinear prediction based on score function

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor European Signal Processing Conference (11è : 2002: Toulouse)
dc.contributor EUSIPCO 2002
dc.contributor.author Solé-Casals, Jordi
dc.contributor.author Monte-Moreno, Enric
dc.date.accessioned 2014-04-09T12:20:32Z
dc.date.available 2014-04-09T12:20:32Z
dc.date.created 2002
dc.date.issued 2002
dc.identifier.uri http://hdl.handle.net/10854/2864
dc.description.abstract The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach. ca_ES
dc.format application/pdf
dc.format.extent 4 p. ca_ES
dc.language.iso eng ca_ES
dc.rights Aquest document està subjecte a aquesta llicència Creative Commons ca_ES
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/ ca_ES
dc.subject.other Processament de la parla ca_ES
dc.title Nonlinear prediction based on score function ca_ES
dc.type info:eu-repo/semantics/conferenceObject ca_ES
dc.rights.accesRights info:eu-repo/semantics/openAccess ca_ES

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