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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 101–135 of 135 papers

TitleStatusHype
The DipInfo-UniTo system for SRST 2018—0
The OSU Realizer for SRST `18: Neural Sequence-to-Sequence Inflection and Incremental Locality-Based Linearization—0
A Structured Variational Autoencoder for Contextual Morphological InflectionCode0
Using English Baits to Catch Serbian Multi-Word Terminology—0
From Phonology to Syntax: Unsupervised Linguistic Typology at Different Levels with Language Embeddings—0
Inflection Generation for Spanish Verbs using Supervised Learning—0
Evaluation of Finite State Morphological Analyzers Based on Paradigm Extraction from Wiktionary—0
Character-based recurrent neural networks for morphological relational reasoning—0
Training Data Augmentation for Low-Resource Morphological Inflection—0
Morphological Inflection Generation with Multi-space Variational Encoder-Decoders—0
Experiments on Morphological Reinflection: CoNLL-2017 Shared Task—0
Seq2seq for Morphological Reinflection: When Deep Learning Fails—0
SU-RUG at the CoNLL-SIGMORPHON 2017 shared task: Morphological Inflection with Attentional Sequence-to-Sequence Models—0
Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction—0
Machine Translation Evaluation for Arabic using Morphologically-enriched Embeddings—0
The Neural Noisy Channel—0
Morphological Inflection Generation with Hard Monotonic AttentionCode0
Online Segment to Segment Neural Transduction—0
MED: The LMU System for the SIGMORPHON 2016 Shared Task on Morphological Reinflection—0
Improving Sequence to Sequence Learning for Morphological Inflection Generation: The BIU-MIT Systems for the SIGMORPHON 2016 Shared Task for Morphological Reinflection—0
Analyzing Learner Understanding of Novel L2 Vocabulary—0
Learning Transducer Models for Morphological Analysis from Example Inflections—0
Nomen Omen. Enhancing the Latin Morphological Analyser Lemlat with an Onomasticon—0
Using longest common subsequence and character models to predict word forms—0
Morphological Inflection Generation Using Character Sequence to Sequence LearningCode0
Inflection Generation as Discriminative String Transduction—0
Ambiguity Resolution for Vt-N Structures in Chinese—0
POS induction with distributional and morphological information using a distance-dependent Chinese restaurant process—0
DeLex, a freely-avaible, large-scale and linguistically grounded morphological lexicon for German—0
JRC-Names: A freely available, highly multilingual named entity resource—0
Controlled Ascent: Imbuing Statistical MT with Linguistic Knowledge—0
Robust multilingual statistical morphological generation models—0
Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors—0
Unsupervised acquisition of concatenative morphology—0
Not as Awful as it Seems: Explaining German Case through Computational Experiments in Fluid Construction Grammar—0
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