Speech enhancement using generalized least absolute deviation estimation

Based on a novel generalized least absolute deviation (GLAD) method, this paper proposes an effective speech enhancement algorithm for the removal of noise from speech signal. Parameters of speech signal modeled as autoregressive (AR) process are well estimated by the GLAD method and thus the speech signal can be well recovered from Kalman filtering. Simulation results show that the proposed GLAD-estimation-based algorithm possesses indeed good speech enhancement performance than the Kalman filtering algorithms based on the second-order estimation and the high-order estimation.