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A similarity value transformation method for probabilistic scoring

Segawa, H. ; Ukita, T.

[1988 Proceedings] 9th International Conference on Pattern Recognition, 1988, p.1225-1209 vol.2

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Título:
A similarity value transformation method for probabilistic scoring
Autor: Segawa, H. ; Ukita, T.
Assuntos: Character recognition ; Distribution functions ; Gaussian distribution ; Pattern recognition ; Performance evaluation ; Research and development ; Speech processing ; Speech recognition
É parte de: [1988 Proceedings] 9th International Conference on Pattern Recognition, 1988, p.1225-1209 vol.2
Descrição: 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.< >
Editor: IEEE Comput. Soc. Press
Idioma: Inglês

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