Odyssey 2010: The Speaker and Language Recognition Workshop
Brno, Czech Republic
Based on the conventional score calibration techniques with gaussian backend and logistic regression of the relative likelihood scores, this paper proposes a method of score calibration specific to a subset of related languages. Detection scores to two related languages are considered as two sources with similar and complementary information. In the proposed score calibration, an optimal linear combination of these two sources is derived. Experiments to NIST LRE 2009 with the proposed method give an equal error rate of 3.33%, which is a 25.2% relative reduction compared with the results from globally calibrated scores. Errors in differentiating two related languages can also be reduced by some modifications in parameter optimization.
Full Paper (PDF)
Bibliographic reference. Ng, Raymond W. M / Leung, Cheung-Chi / Lee, Tan / Ma, Bin / Li, Haizhou (2010): "Detection target dependent score calibration for language recognition", In Odyssey-2010, paper 018.