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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 1–50 of 135 papers

TitleStatusHype
An Extended Sequence Tagging Vocabulary for Grammatical Error CorrectionCode4
Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection EncodingCode1
Applying the Transformer to Character-level TransductionCode1
Exact Hard Monotonic Attention for Character-Level TransductionCode1
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language ProcessingCode1
Learning Transducer Models for Morphological Analysis from Example Inflections—0
Learning to Learn Morphological Inflection for Resource-Poor Languages—0
Leveraging Principal Parts for Morphological Inflection—0
Inflection Generation for Spanish Verbs using Supervised Learning—0
Improving Sequence to Sequence Learning for Morphological Inflection Generation: The BIU-MIT Systems for the SIGMORPHON 2016 Shared Task for Morphological Reinflection—0
JRC-Names: A freely available, highly multilingual named entity resource—0
KU-CST at CoNLL--SIGMORPHON 2018 Shared Task: a Tridirectional Model—0
A Three Step Training Approach with Data Augmentation for Morphological Inflection—0
Probing Subphonemes in Morphology Models—0
Inverting and Modeling Morphological Inflection—0
Exploring Linguistic Probes for Morphological Generalization—0
BME Submission for SIGMORPHON 2021 Shared Task 0. A Three Step Training Approach with Data Augmentation for Morphological Inflection—0
A Comprehensive Comparison of Neural Networks as Cognitive Models of Inflection—0
Ambiguity Resolution for Vt-N Structures in Chinese—0
Can a Transformer Pass the Wug Test? Tuning Copying Bias in Neural Morphological Inflection Models—0
Inflection Generation as Discriminative String Transduction—0
A Resource for Studying Chatino Verbal Morphology—0
Analyzing Learner Understanding of Novel L2 Vocabulary—0
Controlled Ascent: Imbuing Statistical MT with Linguistic Knowledge—0
Copenhagen at CoNLL--SIGMORPHON 2018: Multilingual Inflection in Context with Explicit Morphosyntactic Decoding—0
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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