This article surveys work on Unsupervised Learning of Morphology. We define
Unsupervised Learning of Morphology as the problem of inducing a description (of some …

Morphological segmentation breaks words into morphemes (the basic semantic units). It is a
key component for natural language processing systems. Unsupervised morphological …

One of the great challenges in linguistics and cognitive science is to understand the nature
of the mental representation of language. The precise mechanisms of the mind are …

Word segmentation plays a pivotal role in improving any Arabic NLP application. Therefore,
a lot of research has been spent in improving its accuracy. Off-the-shelf tools, however, are …

ParaMor automatically learns morphological paradigms from unlabelled text, and uses them
to annotate word forms with morpheme boundaries. ParaMor competed in the English and …

In computational linguistics, language models are probabilistic models that predict the
likelihood of words occurring within specific sentences. They are key components of many …

Machine Translation denotes the translation of a text written in one language into another
language performed by a computer program. In times of internet and globalisation, there has …

Grapheme-to-phoneme conversion (g2p) is a core component of any text-to-speech system.
We show that adding simple syllabification and stress assignment constraints, namely 'one …

Non-canonical inflection (suppletion, deponency, heteroclisis, etc.) is extensively studied in
theoretical approaches to morphology. However, these studies often lack practical …

In this article we describe six new web corpora for Turkish, Azerbaijani, Kazakh, Turkmen,
Kyrgyz and Uzbek languages. The data for these corpora was automatically crawled from …