Linguistic Profiles of High Proficiency Mandarin and Hindi Second Language Speakers of English.pdf

Abstract

This dissertation investigates three utterance fluency features and two vocabulary features of 409 speech samples from advanced intermediate and advanced L2 English speakers, who participated in the Oral English Proficiency Test (OEPT) between the year of 2009 and 2015. Among the 409 L2 English speakers, there are 80 L1 Hindi speakers rated as advanced intermediate, 32 L1 Hindi speakers rated as advanced, 286 L1 Mandarin speakers rated as advanced intermediate, and 11 L1 Mandarin speakers rated as advanced.Hierarchical Cluster Analysis (HCA) was conducted and presented four different clusters among all the L2 English speakers. The four different clusters are: (1) Low Mean Syllables per Run (MSR), low Speech Rate (SR), very high Pause Rate (PR), medium Measure of Textual Lexical Diversity (MTLD), and medium percentage of words on the Academic Word List (AWL); (2) Medium Mean Syllables per Run (MSR), medium Speech Rate (SR), high Pause Rate (PR), low Measure of Textual Lexical Diversity (MTLD), and low percentage of words on the Academic Word List (AWL); (3) High Mean Syllables per Run (MSR), high Speech Rate (SR), low Pause Rate (PR), medium Measure of Textual Lexical Diversity (MTLD), and medium percentage of words on the Academic Word List (AWL); (4) Medium Mean Syllables per Run (MSR), medium Speech Rate (SR), low Pause Rate (PR), very high Measure of Textual Lexical Diversity, and very high percentage level of words on the Academic Word List (AWL).Chi-square results show that L2 English speakers’ cluster membership is strongly associated with both their L1 background and level of L2 oral English proficiency. While most of the advanced intermediate L1 Mandarin speakers are in Cluster 1 and Cluster 2, the majority of the advanced intermediate L1 Hindi speakers concentrate in Cluster 3. A large number of advanced L1 Mandarin speakers and L1 Hindi speakers are also located in Cluster 3.Twelve raters were invited to evaluate speech samples representative of the four clusters in terms of accent difference and listener effort. Twelve speakers were selected from the four clusters, whose speech samples have values of the five linguistic features closest to the cluster mean.Multi-facet Rasch Measurement (MFRM) results show that L1 Mandarin speakers generally received lower ratings in accent difference and listener effort. The connection among fluency, vocabulary, and accentedness/listener effort, however, functions differently for L1 Mandarin speakers and L1 Hindi speakers. For advanced intermediate L1 Mandarin speakers, those who speak slower and use more diverse vocabulary and more academic words were evaluated to be less accented, meanwhile costing less listener effort. However, advanced intermediate L1 Hindi speakers were rated as less accented and cost less listener effort when they demonstrate higher fluency measures and lower vocabulary measures.Advanced L2 English speakers, in contrary, received reverse rating results. The advanced L1 Mandarin speaker, who speaks faster and uses less diverse vocabulary and fewer academic words, was evaluated to be less accented and cost less listener effort. However, the advanced L1 Hindi speaker, who speaks slower and uses more diverse vocabulary and more academic words, was rated as less accented and cost less listener effort.This dissertation reemphasizes that holistic rating rubric does not deny the existence of multiple linguistic profiles. Raters are sensitive to different combinations of fluency and vocabulary features even if they have been asked to use a holistic scale. In addition, L2 English speakers may adopt individual strategies to accommodate while delivering, which calls for further pedagogical attention.