Analyzing EFL Learners Phonological Errors Using Speech Recognition Technology Soundtype AI - Artha, Dewi Juni; Bayu, Ardi (Institut Agama Islam Negeri Palopo, 2025)
The purpose of this study is to find out what phonological errors are the most frequent in EFL learners with SoundType AI application. This studyl emlployled a quantitative research design to investigate how advanced Artificial Intelligence technologies imlproved pronouncing qualityl froml the perspective of EFL students. The population for this research includes the EFL learners enrolled in English Education in the Facultyl of Teacher Training and Education at Universitas MLuhamlmladiylah Sumlatera Utara that have finished the Phonologyl course. Sample used for the research wasl 22 EFL learners to ensure statistical significance and allow for subgroup analylsis. The data obtained from the reading test was identified a total of 58 errors across the recordings, with the predominant types being Omissions (20,68%) and mishearings by the speech recognition software (27,43%), Substitutions (18,96%) and Additions (18,96%) and Distortions (15,51%). Overall, these findings underscore the need for targeted interventions to address the specific phonological difficulties faced by EFL learners. Additionally, reading exposes learners to different cultures and perspectives. This cultural awareness enriches their understanding of the world and helps them connect with others more effectively.