Stemming is a process in which the variant word forms are mapped to their base form. It is
among the basic text pre-processing approaches used in Language Modeling, Natural …

What are the units of text that we want to model? From bytes to multi-word expressions, text
can be analyzed and generated at many granularities. Until recently, most natural language …

Morfessor is a family of probabilistic machine learning methods forfinding the morphological
segmentation from raw text data. Recentdevelopments include the development of semi …

We investigate implicit vocabulary learning by adults who are exposed to a language in their
ambient environment. Most New Zealanders do not speak Māori, yet are exposed to it …

Most state-of-the-art systems today produce morphological analysis based only on
orthographic patterns. In contrast, we propose a model for unsupervised morphological …

This article reviews research on the unsupervised learning of morphology, that is, the
induction of morphological knowledge with no prior knowledge of the language beyond the …

We discuss data-driven morphological segmentation, in which word forms are segmented
into morphs, the surface forms of morphemes. Our focus is on a lowresource learning …

Computational morphological segmentation has been an active research topic for decades
as it is beneficial for many natural language processing tasks. With the high cost of manually …

This article presents a comparative study of a subfield of morphology learning referred to as
minimally supervised morphological segmentation. In morphological segmentation, word …

In this work, we present a morphological segmenter for the Mexican indigenous language
Wixarika. Segmentation is fundamental for rich morphological languages, a common aspect …