A modified group vector quantization algorithm for speaker identification
M.F. Abu El-Yazeed, Nemat S. Abdel Kader, Mohammed Mamdouh Zakaria Elhenawy · 2006
In this paper, a modification to the group vector quantization (GVQ) discriminative training algorithm is proposed to train VQ codebooks for closed set speaker identification. The proposed algorithm, referred to as modified GVQ (MGVQ), shifts the decision surfaces between speakers smoothly toward the Bayes limits. This is achieved by varying the learning rate during training iterations. The proposed MGVQ algorithm achieves higher speaker identification rate compared to the standard GVQ.