Challenges Encountered in Turkish Natural Language Processing Studies

TL;DR

This paper discusses the unique challenges of processing Turkish language in NLP due to its complex grammatical and phonological features, and reviews existing techniques and resources for Turkish NLP.

Contribution

It highlights the specific linguistic challenges of Turkish NLP and provides an overview of current techniques and resources developed for this language.

Findings

Turkish's agglutinative structure complicates NLP tasks.

Existing Turkish NLP resources are limited but growing.

Unique phonological rules impact NLP system design.

Abstract

Natural language processing is a branch of computer science that combines artificial intelligence with linguistics. It aims to analyze a language element such as writing or speaking with software and convert it into information. Considering that each language has its own grammatical rules and vocabulary diversity, the complexity of the studies in this field is somewhat understandable. For instance, Turkish is a very interesting language in many ways. Examples of this are agglutinative word structure, consonant/vowel harmony, a large number of productive derivational morphemes (practically infinite vocabulary), derivation and syntactic relations, a complex emphasis on vocabulary and phonological rules. In this study, the interesting features of Turkish in terms of natural language processing are mentioned. In addition, summary info about natural language processing techniques, systems and various sources developed for Turkish are given.