Morphological Inflection Generation with Multi-space Variational Encoder-Decoders

A Structured Variational Autoencoder for Contextual Morphological Inflection

Statistical morphological inflectors are typically trained on fully supervised, type-level data. One remaining open research question is the following: How can we effectively exploit raw, token-level data to improve thei…

Training Strategies for Neural Multilingual Morphological Inflection

This paper presents the submission of team GUCLASP to SIGMORPHON 2021 Shared Task on Generalization in Morphological Inflection Generation. We develop a multilingual model for Morphological Inflection and primarily focus…

Morphological Inflection Generation Using Character Sequence to Sequence Learning

Morphological inflection generation is the task of generating the inflected form of a given lemma corresponding to a particular linguistic transformation. We model the problem of inflection generation as a character sequ…

Improving Sequence to Sequence Learning for Morphological Inflection Generation: The BIU-MIT Systems for the SIGMORPHON 2016 Shared Task for Morphological Reinflection

Morphological Inflection Generation with Hard Monotonic Attention

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…