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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 5175 of 135 papers

TitleStatusHype
Modeling the Graphotactics of Low-Resource Languages Using Sequential GANs0
Morphological Inflection Generation with Multi-space Variational Encoder-Decoders0
Morphological Reinflection in Context: CU Boulder's Submission to CoNLL--SIGMORPHON 2018 Shared Task0
Morphology is not just a naive Bayes – UniMelb Submission to SIGMORPHON 2022 ST on Morphological Inflection0
Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction0
Noise Isn't Always Negative: Countering Exposure Bias in Sequence-to-Sequence Inflection Models0
Nomen Omen. Enhancing the Latin Morphological Analyser Lemlat with an Onomasticon0
Not as Awful as it Seems: Explaining German Case through Computational Experiments in Fluid Construction Grammar0
One Wug, Two Wug+s Transformer Inflection Models Hallucinate Affixes0
Online Segment to Segment Neural Transduction0
Phonological Features for Morphological Inflection0
POS induction with distributional and morphological information using a distance-dependent Chinese restaurant process0
Posterior Attention Models for Sequence to Sequence Learning0
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
SIGMORPHON 2020 Task 0 System Description: ETH Z\"urich Team0
SIGMORPHON 2022 Task 0 Submission Description: Modelling Morphological Inflection with Data-Driven and Rule-Based Approaches0
Surface Realisation Using Full Delexicalisation0
SU-RUG at the CoNLL-SIGMORPHON 2017 shared task: Morphological Inflection with Attentional Sequence-to-Sequence Models0
T\"ubingen-Oslo system at SIGMORPHON shared task on morphological inflection. A multi-tasking multilingual sequence to sequence model.0
The CMU-LTI submission to the SIGMORPHON 2020 Shared Task 0: Language-Specific Cross-Lingual Transfer0
The DipInfo-UniTo system for SRST 20180
The Neural Noisy Channel0
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