Method of modeling single data class from multi-class data

Details Method of modeling single data class from multi-class data Method of modeling single data class from multi-class data

2004-05-13

2008-11-18

Vo, Huyen X. (Department: 2626)

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

C704S243000, C704S245000, C704S244000

Reexamination Certificate

active

07454337

ABSTRACT:
The present invention is a method of modeling a single class of data from data containing multiple classes of data of the same type of data by first receiving a collection of data that includes data from multiple classes of data of the same type where the amount of data of the single class of data exceeds that of any other class of data. A first statistical model of the received collection of data is generated. The collection of data is divided into subsets. Each subset of the speech collection of data is scored using the first statistical model. A set of scores is selected. The subsets corresponding to the selected scores are identified. The identified subsets are combined. A second statistical model of the type of the first statistical model is generated for the combined subsets and used as the model of the single class of data.

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Man-Hung Siu et al., “An Unsupervised, Sequential Learning Algorithm for the Segmentation of Speech Wave Forms With Multiple Speakers,” IEEE, 1992 pp. II-189-II-192.

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