About

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

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Greatest papers with code

Applying the Transformer to Character-level Transduction

20 May 2020shijie-wu/neural-transducer

The transformer has been shown to outperform recurrent neural network-based sequence-to-sequence models in various word-level NLP tasks.

MORPHOLOGICAL INFLECTION TRANSLITERATION

Morphological Inflection Generation with Hard Monotonic Attention

ACL 2017 roeeaharoni/morphological-reinflection

We present a neural model for morphological inflection generation which employs a hard attention mechanism, inspired by the nearly-monotonic alignment commonly found between the characters in a word and the characters in its inflection.

MORPHOLOGICAL INFLECTION

Morphological Inflection Generation Using Character Sequence to Sequence Learning

NAACL 2016 mfaruqui/morph-trans

Morphological inflection generation is the task of generating the inflected form of a given lemma corresponding to a particular linguistic transformation.

MORPHOLOGICAL INFLECTION

Pushing the Limits of Low-Resource Morphological Inflection

IJCNLP 2019 antonisa/inflection

Recent years have seen exceptional strides in the task of automatic morphological inflection generation.

CROSS-LINGUAL TRANSFER MORPHOLOGICAL INFLECTION

Surprisingly Easy Hard-Attention for Sequence to Sequence Learning

EMNLP 2018 sid7954/beam-joint-attention

In this paper we show that a simple beam approximation of the joint distribution between attention and output is an easy, accurate, and efficient attention mechanism for sequence to sequence learning.

IMAGE CAPTIONING MORPHOLOGICAL INFLECTION

SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection

WS 2020 sigmorphon2020/task0-data

Systems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages.

MORPHOLOGICAL INFLECTION

A Latent Morphology Model for Open-Vocabulary Neural Machine Translation

ICLR 2020 d-ataman/lmm

Translation into morphologically-rich languages challenges neural machine translation (NMT) models with extremely sparse vocabularies where atomic treatment of surface forms is unrealistic.

MACHINE TRANSLATION MORPHOLOGICAL INFLECTION