Multi-resolution form of SVD for text-independent speaker recognition

摘要

A text-independent speaker recognition system based on multi-resolution singular value decomposition (MSVD) is proposed. The MSVD is applied to the speaker data compression and feature extraction not at the square matrix. Our results have shown that this MSVD introduced better performance than the other Karhunen–Loeve transform with respect to the percentages of recognition.