Inflectional variation is a common feature of World Englishes such as Colloquial Singapore
English and African American Vernacular English. Although comprehension by human …

With easier access to powerful compute resources, there is a growing trend in the field of AI
for software development to develop larger and larger language models (LLMs) to address a …

In this paper we present the first full morphological analysis and disambiguation system for
Gulf Arabic. We use an existing state-of-the-art morphological disambiguation system to …

This work treats the paradigm discovery problem (PDP), the task of learning an inflectional
morphological system from unannotated sentences. We formalize the PDP and develop …

Building a system for morphological processing is a challenging task in morphologically
complex languages like Arabic. Although there are some deep learning based models that …

Representation learning has played a crucial role in various natural language processing
tasks since the advent of deep neural networks. Recent research shows that word …

One core challenge facing morphological inflection systems is capturing language-specific
morphophonological changes. This is particularly true of languages like Arabic which are …

There is high hope that corpus-based approaches to language complexity will contribute to
explaining linguistic diversity. Several complexity indices have consequently been proposed …

Resource-limited and morphologically rich languages pose many challenges to natural
language processing tasks. Their highly inflected surface forms inflate the vocabulary size …

Linguistics as a science is concerned with classifying languages according to different
properties in order to understand how language works. There are several well-known ways …