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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 76–100 of 135 papers

TitleStatusHype
The CMU-LTI submission to the SIGMORPHON 2020 Shared Task 0: Language-Specific Cross-Lingual Transfer—0
The DipInfo-UniTo system for SRST 2018—0
The Neural Noisy Channel—0
The NYU-CUBoulder Systems for SIGMORPHON 2020 Task 0 and Task 2—0
The NYU System for the CoNLL--SIGMORPHON 2018 Shared Task on Universal Morphological Reinflection—0
The OSU/Facebook Realizer for SRST 2019: Seq2Seq Inflection and Serialized Tree2Tree Linearization—0
The OSU Realizer for SRST `18: Neural Sequence-to-Sequence Inflection and Incremental Locality-Based Linearization—0
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection—0
The UniMelb Submission to the SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection—0
Training Data Augmentation for Low-Resource Morphological Inflection—0
Training Strategies for Neural Multilingual Morphological Inflection—0
Transliteration for Cross-Lingual Morphological Inflection—0
UniMorph 4.0: Universal Morphology—0
University of Illinois Submission to the SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection—0
(Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models’ Performance—0
Unsupervised acquisition of concatenative morphology—0
Using English Baits to Catch Serbian Multi-Word Terminology—0
Using longest common subsequence and character models to predict word forms—0
Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors—0
UZH at CoNLL--SIGMORPHON 2018 Shared Task on Universal Morphological Reinflection—0
Well-Defined Morphology is Sentence-Level Morphology—0
Were We There Already? Applying Minimal Generalization to the SIGMORPHON-UniMorph Shared Task on Cognitively Plausible Morphological Inflection—0
What can we gain from language models for morphological inflection?—0
Probing Subphonemes in Morphology Models—0
What transfers in morphological inflection? Experiments with analogical models—0
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