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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

Showing 101125 of 135 papers

TitleStatusHype
Robust multilingual statistical morphological generation models0
Searching for Search Errors in Neural Morphological Inflection0
Seq2seq for Morphological Reinflection: When Deep Learning Fails0
Sigmorphon 2019 Task 2 system description paper: Morphological analysis in context for many languages, with supervision from only a few0
A Structured Variational Autoencoder for Contextual Morphological InflectionCode0
A Study of Morphological Robustness of Neural Machine TranslationCode0
OOVs in the Spotlight: How to Inflect them?Code0
Finding the way from ä to a: Sub-character morphological inflection for the SIGMORPHON 2018 Shared TaskCode0
Understanding Compositional Data Augmentation in Typologically Diverse Morphological InflectionCode0
A Latent Morphology Model for Open-Vocabulary Neural Machine TranslationCode0
Minimal Supervision for Morphological InflectionCode0
An Investigation of Noise in Morphological InflectionCode0
Can a Neural Model Guide Fieldwork? A Case Study on Morphological Data CollectionCode0
Systematic Inequalities in Language Technology Performance across the World's LanguagesCode0
IIT(BHU)--IIITH at CoNLL--SIGMORPHON 2018 Shared Task on Universal Morphological ReinflectionCode0
CLUZH at SIGMORPHON 2022 Shared Tasks on Morpheme Segmentation and Inflection GenerationCode0
Morphological Inflection: A Reality CheckCode0
Morphological Inflection Generation Using Character Sequence to Sequence LearningCode0
Systematic Inequalities in Language Technology Performance across the World’s LanguagesCode0
Morphological Inflection Generation with Hard Monotonic AttentionCode0
Morphological Inflection with Phonological FeaturesCode0
Interpretability for Morphological Inflection: from Character-level Predictions to Subword-level RulesCode0
Pushing the Limits of Low-Resource Morphological InflectionCode0
Eeny, meeny, miny, moe. How to choose data for morphological inflectionCode0
SimpleNLG-ZH: a Linguistic Realisation Engine for MandarinCode0
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