Abstract
Automatic speech recognition system is one of the parts of the multimodal dialogue system. It is necessary to create correct vocabulary and to generate suitable language model for this purpose. The main aim of this article is to describe a process of building statistical models of the Slovak language with large vocabulary trained on the text data gathered mainly from Internet sources. Several smoothing techniques for different sizes of vocabulary have been used in order to obtain an optimal model of the Slovak language. We have also employed pruning technique based on relative entropy for size reduction of a language model to find the maximum threshold of pruning with minimum degradation in recognition accuracy. Tests were performed by the decoder based on the HTK Toolkit.
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Staš, J., Hládek, D., Pleva, M., Juhár, J. (2011). Slovak Language Model from Internet Text Data. In: Esposito, A., Esposito, A.M., Martone, R., Müller, V.C., Scarpetta, G. (eds) Toward Autonomous, Adaptive, and Context-Aware Multimodal Interfaces. Theoretical and Practical Issues. Lecture Notes in Computer Science, vol 6456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18184-9_29
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DOI: https://doi.org/10.1007/978-3-642-18184-9_29
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