Recovery of LSP Coefficients in VoIP Systems

In order to deliver real time, high quality voice services, VoIP system designers must tackle the packet-loss problems that are inherent in packet-based networks. To combat the inevitable speech quality deterioration resulting from the loss of transmitted packets of speech information, techniques that provide estimates of the lost information that is needed by the speech recovery process are of considerable interest. Furthermore, in future VoIP systems employing LPC based speech coders, a significant percentage of the coded speech information will represent the values of LPC coefficients and thus a new probabilistic approach for estimating missing LPC filter coefficients is presented in this paper. This approach employs a new formulation of LSP recovery system architecture where dependent-multiple Hidden Markov Models with Discrete Densities (DM-HMM-D) operate in parallel. Each HMM processes sequences of received quantized vectors of LSP coefficients and, while allowing for the modeling of the interdependencies that exist between LPC coefficients, resulting maximum likelihood observation probabilities are used to provide the required estimates of missing LSPs. The proposed missing parameters estimation technique is generic and initial experimental results demonstrate its considerable potential in improving the quality of LPC based decoded speech in VoIP applications).