ODYSSEY 2004 - The Speaker and Language Recognition Workshop

May 31 - June 3, 2004
Toledo, Spain

Language Recognition with Support Vector Machines

William M. Campbell, Elliot Singer, Pedro A. Torres-Carrasquillo, Douglas A. Reynolds

MIT Lincoln Laboratory, Lexington, MA, USA

Support vector machines (SVMs) have become a popular tool for discriminative classification. Powerful theoretical and computational tools for support vector machines have enabled significant improvements in pattern classification in several areas. An exciting area of recent application of support vector machines is in speech processing. A key aspect of applying SVMs to speech is to provide a SVM kernel which compares sequences of feature vectors - a sequence kernel. We propose the use of sequence kernels for language recognition. We apply our methods to the NIST 2003 language evaluation task. Results demonstrate the potential of the new SVM methods.

Full Paper

Bibliographic reference.  Campbell, William M. / Singer, Elliot / Torres-Carrasquillo, Pedro A. / Reynolds, Douglas A. (2004): "Language recognition with support vector machines", In ODYS-2004, 285-288.