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Showing 1 to 4 of 4 for “"morphologically rich languages"”.

  1. Learning Morphology for Open-Vocabulary Neural Machine Translation

    … bottleneck on performance, especially in morphologically-rich languages, where the word vocabulary tends to be huge and sparse. In this dissertation, we propose to solve the vocabulary limitation problem in neural machine translation by integrating morphology learning within the …

    trento Repository record for Learning Morphology for Open-Vocabulary Neural Machine Translation (opens in a new tab)

  2. Semantic role labeling using rich morphological features

    … may provide substantial improvements to morphologically rich languages. I demonstrate that the incorporation of rich-morphological features substantially outperform the established lexico-syntactic featuresets of standard SRL systems. A principled feature selection algorithm for SRL is …

    uiuc Repository record for Semantic role labeling using rich morphological features (opens in a new tab)

  3. Towards a machine-learning architecture for lexical functional grammar parsing

    … at producing wide-coverage grammars of human languages. Initial efforts in this field produced relatively shallow linguistic representations such as phrase-structure trees, which only encode constituent structure. Recent work on inducing deep grammars from treebanks addresses this shortcoming …

    dcu Repository record for Towards a machine-learning architecture for lexical functional grammar parsing (opens in a new tab)

  4. Morphological competence in neural natural language processing

    In case-marking languages (CMLs), such as Polish or Finnish, a substantial portion of grammatical information is expressed at the word-level. The word-forms provide information about their inherent properties, like tense or mood, but also encode information about relations between the words. This …

    cambridge Repository record for Morphological competence in neural natural language processing (opens in a new tab)