Crosslinguistic Influence in the Discrimination of Korean Stop Contrast by Heritage Speakers and Second Language Learners

Abstract

The present study examines the extent of crosslinguistic influence from English as a dominant language in the perception of the Korean lenis–aspirated contrast among Korean heritage speakers in the United States (N = 20) and English-speaking learners of Korean as a second language (N = 20), as compared to native speakers of Korean immersed in the first language environment (N = 20), by using an AX discrimination task. In addition, we sought to determine whether significant dependencies could be observed between participants’ linguistic background and experiences and their perceptual accuracy in the discrimination task. Results of a mixed-effects logistic regression model demonstrated that heritage speakers outperformed second language learners with 85% vs. 63% accurate discrimination, while no significant difference was detected between heritage speakers and first language-immersed native speakers (85% vs. 88% correct). Furthermore, higher verbal fluency was significantly predictive of greater perceptual accuracy for the heritage speakers. The results are compatible with the interpretation that the influence of English on the discrimination of the Korean laryngeal contrast was stronger for second language learners of Korean than for heritage speakers, while heritage speakers were not apparently affected by dominance in English in their discrimination of Korean lenis and aspirated stops.

The perception of English vowels by native Korean and Mandarin speakers

“…For each trial, participants heard an audio clip containing two words consecutively, with a 200 ms gap between the words in a pair, and were then asked to indicate whether 'the two vowels in the words' they heard were different or the same. The 200 ms gap was chosen based on similar AX discrimination task studies (Seo et al, 2022). The response was not timed, but participants were unable to replay the audio.…”

“…A logistic regression mixed-effects model was chosen to analyze the data based on previous studies with similar perceptual discrimination tasks (Ryu, 2018;Seo et al, 2022). In this model perceptual accuracy, coded as '1' (correct response) or '0' (incorrect response), as a binary categorical dependent variable.…”