Design and Analysis of Speech Processing Using Kalman Filtering
Speech processing is used widely in every day's applications that most people take for granted, such as network wire lines, cellular telephony, telephony system and telephone answering machines. Due to its popularity and increasing of demand, engineers are trying various approaches of improving the process. One of the methods for improving the process is Kalman filtering. Kalman filtering has now become a popular filtering technique for estimating and resolving redundant errors contained in speech. The objective of this paper is to generate a reconstructed output speech signal from the input signal involving the application of a Kalman filter estimation technique. In this paper, Kalman filter is used to estimate the parameters of the AutoRegressive (AR) process and represented in the state-space domain.