Abstract
Most commercialized speech recognition systems that have a large capacity and high recognition rates are a type of speaker dependent isolated word recognition systems. In order to extend the scope of recognition, it is necessary to increase the number of words that are to be searched. However, it shows a problem that exhibits a decrease in the system performance according to the increase in the number of words. This paper defines the context information that affects speech recognition in a ubiquitous environment to solve such a problem and designs a new speech recognition system that demonstrates better performances than the existing system by establishing a word model domain of a speech recognition system. © International Federation for Information Processing 2007.
Cite
CITATION STYLE
Kim, J. H., Kang, U. G., Rim, K. W., & Lee, J. H. (2007). Speech recognition system using DHMMs based on ubiquitous environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4761 LNCS, pp. 213–222). Springer Verlag. https://doi.org/10.1007/978-3-540-75664-4_21
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