Automatic Lexical Simplification for Turkish

TL;DR

This paper introduces the first automatic lexical simplification system for Turkish, leveraging pretrained BERT models and morphological features to handle the language's complexity.

Contribution

It presents a novel text simplification pipeline specifically designed for Turkish, addressing its morphological richness and resource limitations.

Findings

Effective simplification of Turkish words using the proposed method

Improved grammatical correctness and semantic appropriateness

Addresses challenges of low-resource, morphologically rich languages

Abstract

In this paper, we present the first automatic lexical simplification system for the Turkish language. Recent text simplification efforts rely on manually crafted simplified corpora and comprehensive NLP tools that can analyse the target text both in word and sentence levels. Turkish is a morphologically rich agglutinative language that requires unique considerations such as the proper handling of inflectional cases. Being a low-resource language in terms of available resources and industrial-strength tools, it makes the text simplification task harder to approach. We present a new text simplification pipeline based on pretrained representation model BERT together with morphological features to generate grammatically correct and semantically appropriate word-level simplifications.