Pronunciation Assessment: Traditional vs Modern Modes

Abstract

This article discusses the significance of pronunciation in linguistic competence and its role in effective communication for English speakers. It highlights the potential issues arising from human-rated pronunciation assessments, including inconsistency and bias. To overcome these challenges, the article examines the adoption of AI-powered platforms in pronunciation assessment. These platforms offer rapid results while maintaining high validity standards. They rely on technologies like Automatic Speech Recognition (ASR) and speech analysis programs to evaluate pronunciation skills based on suprasegmental features such as stress and intonation.The article also explores the future of AI-powered pronunciation assessment, which presents both opportunities and challenges. These platforms offer scalability, consistency, and personalized feedback, enhancing the learning experience. However, they must address issues related to scoring model validity, speech data diversity, ethical concerns, and the integration of human and machine feedback. In conclusion, the adoption of AI in pronunciation assessment is transforming language testing, offering advantages in terms of efficiency and accessibility while posing challenges related to validity and ethical considerations. Ongoing research and development will be essential to ensure AI-powered platforms meet the evolving needs of language learners and educators in large-scale language tests.