A similarity value transformation method for probabilistic scoring

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 simi...

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Bibliographic Details
Published inPattern Recognition, 9th International Conference on, 1988: Proceedings pp. 1225 - 1209 vol.2
Main Authors Segawa, H., Ukita, T.
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE Comput. Soc. Press 06.01.2003
Subjects
Character recognition
Distribution functions
Gaussian distribution
Pattern recognition
Performance evaluation
Research and development
Speech processing
Speech recognition
Online AccessGet full text
ISBN9780818608780
0818608781
DOI10.1109/ICPR.1988.28477

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Summary: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.< >
ISBN:9780818608780
0818608781
DOI:10.1109/ICPR.1988.28477