Morphological reinflection with conditional random fields and unsupervised features

Unlabeled Data for Morphological Generation With Character-Based Sequence-to-Sequence Models

We present a semi-supervised way of training a character-based encoder-decoder recurrent neural network for morphological reinflection, the task of generating one inflected word form from another. This is achieved by usi…

Neural Multi-Source Morphological Reinflection

We explore the task of multi-source morphological reinflection, which generalizes the standard, single-source version. The input consists of (i) a target tag and (ii) multiple pairs of source form and source tag for a le…

Single-Model Encoder-Decoder with Explicit Morphological Representation for Reinflection

Morphological reinflection is the task of generating a target form given a source form, a source tag and a target tag. We propose a new way of modeling this task with neural encoder-decoder models. Our approach reduces t…

Painless Semi-Supervised Morphological Segmentation using Conditional Random Fields

Supervised Morphological Segmentation in a Low-Resource Learning Setting using Conditional Random Fields