Морфологический теггер

Speech recognition in many morphologi- cally rich languages suffers from a very high out-of-vocabulary (OOV) ratio. Earlier work has shown that vocabulary decomposition methods can practically solve this problem for …...

Sanskrit, the classical language of India, presents specific challenges for computational linguistics: exact phonetic transcription in writing that obscures word boundaries, rich morphology and an enormous corpus, among others. Recent …...

The many differences between Dialectal Ara- bic and Modern Standard Arabic (MSA) pose a challenge to the majority of Arabic natural language processing tools, which are designed for MSA. In …...

AbstractArabic dialects present a special problem for natural language processing because there are few resources, they have no standard orthography, and have not been studied much. However, as more and …...

Morphologically rich languages often lack the annotated linguistic resources required to develop accurate natural language pro- cessing tools. We propose models suitable for training morphological taggers with rich tagsets for …...

AbstractA lack of datasets for spelling and grammatical error correction in Icelandic, along with language-specific issues, has caused a dearth of spell and grammar checking systems for the language. We …...

AbstractMost linguistic studies of Judeo-Arabic, the ensemble of dialects spoken and written by Jews in Arab lands, are qualitative in nature and rely on laborious manual annotation work, and are …...