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Voiced/Unvoiced classification recovery in the speech decoder based on GMM

Voiced/Unvoiced (V/U) classification is an important parameter in low bit-rate speech coding algorithms. An algorithm that recovers the V/U classification from the linear prediction coding (LPC) coefficients and the gain in the speech decoder is proposed. Two Gaussian mixture models (GMM) are employed to model the joint probability of these parameters and to perform the V/U estimation. Experiments show the performance improvements of the proposed algorithm over the V/U classifier used in mixed excitation LPC vocoder (MELP). The proposed algorithm operates only at the receiving end and saves all the bits originally used for V/U quantization.