Nonlinear formant-pitch prediction using recurrent neural networks
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Publisher
European Signal Processing Conference, EUSIPCO
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info:eu-repo/semantics/closedAccess
Abstract
In this study, a parallel structure is proposed for the nonlinear formant and pitch prediction of speech signals using Recurrent Neural Networks (RNN) The well known Real Time Recurrent Learning (RTRL) algorithm is used as the learning algorithm. Its performance is evaluated in terms of the meansquare error and sensitivity to pitch errors through extensive computer simulations and compared to the combined formant-pitch RNN predictor and to the linear predictor. © 2015 European Signal Processing Conference, EUSIPCO. All rights reserved.
Description
8th European Signal Processing Conference, EUSIPCO 1996 -- 1996-09-10 through 1996-09-13 -- Trieste -- 115734
Keywords
Continuous speech recognition, Learning algorithms, Signal processing, Linear predictors, Parallel structures, Pitch errors, Real time recurrent learning algorithms, Recurrent neural network (RNN), Speech signals, Recurrent neural networks
Journal or Series
European Signal Processing Conference
