Text-independent speaker recognition using graph matching

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• 作者：Ville Hautamä ; ki ; Tomi Kinnunen ; Pasi Frä ; nti
• 关键词：Affine transformation invariance ; Graph matching ; Structural matching ; kNN graph ; Clustering ; Speaker recognition
• 刊名：Pattern Recognition Letters
• 出版年：2008
• 期刊代码：101_01678655
• 类别：cp
• 出版时间：1 July 2008
• 卷：29
• 期：9
• 页码：1427-1432
• 文件大小：752 K

摘要

Technical mismatches between the training and matching conditions adversely affect the performance of a speaker recognition system. In this paper, we present a matching scheme which is invariant to feature rotation, translation and uniform scaling. The proposed approach uses a neighborhood graph to represent the global shape of the feature distribution. The reference and test graphs are aligned by graph matching and the match score is computed using conventional template matching. Experiments on the NIST-1999 SRE corpus indicate that the method is comparable to conventional Gaussian mixture model (GMM) and vector quantization (VQ)-based approaches.