Title :
ADPCM with nonlinear prediction
Author :
Faundez-Zanuy, Marcos ; Oliva-Suarez, Oscar
Abstract :
Many speech coders are based on linear prediction coding (LPC), nevertheless with LPC is not possible to model the nonlinearities present in the speech signal. Because of this there is a growing interest for nonlinear techniques. In this paper we discuss ADPCM schemes with a nonlinear predictor based on neural nets, which yields an increase of 1-2.5dB in the SEGSNR over classical methods. This paper will discuss the block-adaptive and sample-adaptive predictions.
Keywords :
linear codes; neural nets; speech coding; ADPCM scheme; LPC; linear prediction coding; neural nets; nonlinear predictor; speech coders; speech signal; Neural networks; Predictive models; Quantization (signal); Speech; Speech coding; Switches; Training;
Conference_Titel :
Signal Processing Conference (EUSIPCO 1998), 9th European
Conference_Location :
Rhodes
Print_ISBN :
978-960-7620-06-4
