We present results of probabilistic tagging of Czech texts in order to show how these techniques work for one of the highly morphologically ambiguous inflective languages. After d...
Speech recognition of inflectional and morphologically rich languages like Czech is currently quite a challenging task, because simple n-gram techniques are unable to capture impo...
We improve the quality of statistical machine translation (SMT) by applying models that predict word forms from their stems using extensive morphological and syntactic information...
One of the most important steps in text processing and information retrieval is stemming—reducing of words to stems expressing their base meaning, e.g., bake, baked, bakes, bakin...
Alexander F. Gelbukh, Mikhail Alexandrov, Sang-Yon...