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Title: | Gaussian selection algorithm in Continuous Speech Recognition | Authors: | Popović, Boris Janev M. Delić, Vlado |
Issue Date: | 1-Dec-2012 | Journal: | 2012 20th Telecommunications Forum, TELFOR 2012 - Proceedings | Abstract: | Clustering of Gaussian mixture components, i.e. Hierarchical Gaussian mixture model clustering (HGMMC) is a key component of Gaussian selection (GS) algorithm, used in order to increase the speed of a Continuous Speech Recognition (CSR) system, without any significant degradation of its recognition accuracy. In this paper a novel Split-and-Merge (S&M) HGMMC algorithm is applied to GS, in order to achieve a better trade-off between speed and accuracy in a CSR task. The algorithm is further improved by introducing model selection in order to obtain the best possible trade-off between recognition accuracy and computational load in a GS task applied within an actual recognition system. At the end of the paper we discuss additional improvements towards finding the optimal setting for the Gaussian selection scheme. © 2012 IEEE. | URI: | https://open.uns.ac.rs/handle/123456789/9461 | ISBN: | 9781467329842 | DOI: | 10.1109/TELFOR.2012.6419307 |
Appears in Collections: | FTN Publikacije/Publications |
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