USING SPEECH CORPORA TO IDENTIFY COMMON PRONUNCIATION CHALLENGES FOR ESL LEARNERS

Abstract

Pronunciation is a critical aspect of second language acquisition, yet it remains a challenge for many ESL learners due to the complex interplay of phonetic differences between the first and second languages, limited exposure to native-like speech, and the lack of focused pronunciation training. This study explores the use of speech corpora, specifically the L2-ARCTIC corpus, to identify common pronunciation challenges faced by ESL learners. The corpus includes speech data from a diverse group of non-native speakers, providing a rich source of phonetic information for error analysis. Through systematic examination, this research identifies recurring patterns of mispronunciations, such as vowel substitutions, consonant omissions, and incorrect stress placement. By comparing learner speech with native English speech patterns, the study highlights the impact of L1 interference and proficiency levels on pronunciation errors. The findings suggest that corpus-based approaches can provide valuable insights for more targeted and individualized pronunciation instruction. The study’s implications emphasize the potential for integrating speech corpora into ESL teaching methodologies, offering practical strategies to enhance pronunciation training using data-driven techniques.