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Morphological Inflection

Morphological Inflection is the task of generating a target (inflected form) word from a source word (base form), given a morphological attribute, e.g. number, tense, and person etc. It is useful for alleviating data sparsity issues in translating morphologically rich languages. The transformation from a base form to an inflected form usually includes concatenating the base form with a prefix or a suffix and substituting some characters. For example, the inflected form of a Finnish stem eläkeikä (retirement age) is eläkeiittä when the case is abessive and the number is plural.

Source: Tackling Sequence to Sequence Mapping Problems with Neural Networks

Papers

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Showing 26–50 of 135 papers

TitleStatusHype
Cross-lingual morphological inflection with explicit alignment—0
DeLex, a freely-avaible, large-scale and linguistically grounded morphological lexicon for German—0
Do RNN States Encode Abstract Phonological Processes?—0
Do RNN States Encode Abstract Phonological Alternations?—0
Autoregressive Modeling with Lookahead Attention—0
Evaluation of Finite State Morphological Analyzers Based on Paradigm Extraction from Wiktionary—0
BME-HAS System for CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection—0
Ensembles of Neural Morphological Inflection Models—0
Ensemble Self-Training for Low-Resource Languages: Grapheme-to-Phoneme Conversion and Morphological Inflection—0
Experiments on Morphological Reinflection: CoNLL-2018 Shared Task—0
Experiments on Morphological Reinflection: CoNLL-2017 Shared Task—0
Backtranslation in Neural Morphological Inflection—0
Exploring Looping Effects in RNN-based Architectures—0
Improving Low-Resource Morphological Inflection via Self-Supervised Objectives—0
Exploring Neural Architectures And Techniques For Typologically Diverse Morphological Inflection—0
Fast and Accurate Reordering with ITG Transition RNN—0
Finding the way from \"a to a: Sub-character morphological inflection for the SIGMORPHON 2018 shared task—0
Character-based recurrent neural networks for morphological relational reasoning—0
From Phonology to Syntax: Unsupervised Linguistic Typology at Different Levels with Language Embeddings—0
Generalizing Morphological Inflection Systems to Unseen Lemmas—0
Getting More Data for Low-resource Morphological Inflection: Language Models and Data Augmentation—0
How do we get there? Evaluating transformer neural networks as cognitive models for English past tense inflection—0
Contextualization of Morphological Inflection—0
Improved pronunciation prediction accuracy using morphology—0
IPS-WASEDA system at CoNLL--SIGMORPHON 2018 Shared Task on morphological inflection—0
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