Syllabification in English through AI: A Comparative Study of ChatGPT and Gemini

This paper examines the English language syllabification task, focusing on two advanced Artificial Intelligence (AI) models: ChatGPT and Gemini. Syllabification is one of the first things one learns about phonology; it is the process of breaking words apart into their smallest phonological units, syllables. It is an essential idea that we will consider for a number of purposes, including language learning, speech synthesis, or computational linguistics, that the systematic view of syllables might help you to teach engineering development in voice recognition and the reaction process. The analysis of transcribed words is based on Peter Roach (RP) in (2009) and the Oxford Advanced Learner's Dictionary (2020). It utilizes a carefully selected dataset comprising 100 multisyllabic English words, covering all lexical categories. Then the words have been carefully analyzed to evaluate the accuracy of segmentation in the syllabification process. Through a comprehensive comparative analysis, the study identified the commonalities and differences in the syllabification patterns exhibited by the two AI models. This study significantly contributes to phonemic research, demonstrating the potential applications and limitations of AI in linguistic contexts, and shows that ChatGPT is more accurate in the task of syllabification than Gemini.