Analysis of morph-based language modeling and speech recognition in Slovak

Abstract

The inflection of the Slovak language causes a large number of unique word forms, which produces not only a large vocabulary, but also a number of out-of-vocabulary words. Morph-based language models solve this problem by decomposition of inflected word forms into small sub-word units and resolve the general problem of sparsity the training data. In this paper, we present several rule-based and data-driven approaches to the automatic segmentation of words into morphs. These data are later used in the modeling of the Slovak language for large vocabulary continuous speech recognition. Preliminary results show a significant decrease in the number of out-of-vocabulary words and reduction of resultant language model perplexity.