DocumentCode
701544
Title
Nonlinear formant-pitch prediction using Recurrent Neural Networks
Author
Varoglu, Ekrem ; Hacioglu, Kadri
Author_Institution
Department of Electrical and Electronics Engineering Eastern Mediterranean University, Gazi Magosa, Mersin-10, Turkey
fYear
1996
fDate
10-13 Sept. 1996
Firstpage
1
Lastpage
4
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 mean-square error and sensitivity to pitch errors through extensive computer simulations and compared to the combined formant-pitch RNN predictor and to the linear predictor.
Keywords
Computational complexity; Neurons; Prediction algorithms; Predictive models; Recurrent neural networks; Sensitivity; Speech;
fLanguage
English
Publisher
ieee
Conference_Titel
European Signal Processing Conference, 1996. EUSIPCO 1996. 8th
Conference_Location
Trieste, Italy
Print_ISBN
978-888-6179-83-6
Type
conf
Filename
7083271
Link To Document