This paper investigates factors contributing to the performance of the POS Tagger for Tagalog language. Tagalog, a morphologically rich language, exhibits complex morphological structure, makes use of morphological information in determining parts of speech of the word, aspect and voice. As word feature information plays important role in efficient tagging, tag set definition capturing word inf...

The paper presents an integrated environment for morphological analysis of word-forms of the Slovene language. The system consists of a lexicon input and maintenance module, a lexicon output module for accessing lexical word forms, a two-level rule compiler and a two-level morphological analysis/synthesis unit. The basic paradigms and lexical alternations of word forms are handled by the lexico...

The paper presents an integrated environment for morphological analysis of word-forms of the Slovene language. The system consists of a lexicon input and maintenance module, a lexicon output module for accessing lexical word forms, a two-level rule compiler and a two-level morphological analysis/synthesis unit. The basic paradigms and lexical alternations of word forms are handled by the lexico...

Bilinguals recognize words with shared morphology and phonology cross-linguistically (i.e., cognates) faster than that do not have these characteristics. Moreover, higher phonological overlap in cognates enhances the effects, which suggests eases word recognition. However, it is currently unclear whether compete purely morphologically before spoken recognition within language proficiency L2 mod...

We present a novel method of statistical morphological generation, i.e. the prediction of inflected word forms given lemma, part-of-speech and morphological features, aimed at robustness to unseen inputs. Our system uses a trainable classifier to predict “edit scripts” that are then used to transform lemmas into inflected word forms. Suffixes of lemmas are included as features to achieve robust...

We present a new morphological analysis model that considers semantic plausibility of word sequences by using a recurrent neural network language model (RNNLM). In unsegmented languages, since language models are learned from automatically segmented texts and inevitably contain errors, it is not apparent that conventional language models contribute to morphological analysis. To solve this probl...

This paper explains how semantic hypergraphs are used to construct ontological models of morphological rules in the Kazakh language. The nodes within these graphs represent semantic features (morphological concepts) and the edges within represent the relationships between these features. Word forms within the hypergraph structure are described in trees which are converted into linear parenthesi...

Morphological learning approaches have been successfully applied to morphological tasks in computational linguistics including morphological analysis and generation. We take a new look at the fundamental properties of associative memory along with the power of turing machine and show how it can be adopted for natural language processing. The ability to store and recall stored patterns based on ...