Title :
Nonlinear prediction for speech coding using radial basis functions
Author :
Díaz-de-María, Fernando ; Figueiras-Vidal, Anibal R.
Author_Institution :
Dept. de Electron., Cantabria Univ., Santander, Spain
Abstract :
Radial basis functions (RBF) networks constitute an interesting option for dealing with nonlinear prediction of speech because they provide a regularized solution. They can guarantee the stability of the corresponding synthesis scheme; consequently, they are used in code excited nonlinear prediction (CENP) coders. This approach is presented, and some simulations examples show its advantage in the prediction performance. The practical implementations of CENP coders are also addressed
Keywords :
feedforward neural nets; multilayer perceptrons; prediction theory; speech coding; speech processing; speech synthesis; vocoders; CENP coders; code excited nonlinear prediction coders; nonlinear prediction; prediction performance; radial basis functions networks; regularized solution; simulations examples; stability; synthesis scheme; Human voice; Network synthesis; Predictive coding; Predictive models; Quantization; Signal mapping; Speech coding; Speech synthesis; Stability; Switches; Telecommunications;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479812
