Odyssey 2010: The Speaker and Language Recognition Workshop

Brno, Czech Republic
28 June – 1 July 2010

PCA-based Feature Extraction for Phonotactic Language Recognition

Tomás Mikolov, Oldrich Plchot, Ondrej Glembek, Lukás Burget, Jan Cernocký (1)

(1) Brno University of Technology

Phonotactic language recognition is one of major techniques used for automatic recognition of spoken languages. We propose a feature extraction technique based on PCA to be used with SVM-based systems. This technique improves speed of the training, in some cases more than 1000 times, allowing systems to be effectively trained on much larger data sets. Speed-up of the test phase can be even greater, which makes the resulting systems much more useful for processing large amounts of data. We report our results on NIST LRE 2009 task.

Full Paper (PDF)

Bibliographic reference.  Mikolov, Tomás / Plchot, Oldrich / Glembek, Ondrej / Burget, Lukás / Cernocký, Jan (2010): "PCA-based Feature Extraction for Phonotactic Language Recognition", In Odyssey-2010, paper 042.