A KALMAN FILTERING APPROACH TO GMM PREDICTIVE CODING OF LSFS FOR PACKET LOSS CONDITIONS
Gaussian Mixture Model (GMM)-based vector quantization of Line Spectral Frequencies (LSFs) has gained wide acceptance in speech coding. In predictive coding of LSFs, the GMM approach utilizing Kalman filtering principles to account for quantization noise has been shown to perform better than a baseline GMM Recursive Coder approaches for both clean and packet loss conditions at roughly the same com
