Automatic Lexical Simplification for Turkish
This addresses the need for text simplification tools in Turkish, an incremental advancement as it adapts existing methods to a new language context.
The authors tackled the problem of automatic lexical simplification for Turkish, a low-resource language, by developing a pipeline using BERT and morphological features, achieving grammatically correct and semantically appropriate word-level simplifications.
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.