A similarity value transformation method for probabilistic scoring
H. Segawa, Teruhiko Ukita · 2003
A method to transform a similarity measure into a probability measure which indicates the reliability of classification is shown. A statistical model for the similarity value distribution is introduced for efficient estimation from a small number of samples. It is theoretically derived that the similarity value distribution in the multiple similarity method belongs to the family of Gamma distribution under this model. Several experiments were carried out to give support to the similarity value distribution model. It is shown that the estimated posterior probability using the proposed method proves effective for pattern recognition, such as connected-digit speech recognition.>