Kev Message Extraction Failure In High-speed E-C Simultaneous Interpretion And Its Coping Strategies

This paper explores the key message extraction failure in high-speed English-Chinese (E-C) Simultaneous Interpretation (SI) and the relevant coping strategies.In the first part, Daniel Gile’s Effort Model is introduced to explain the information processing process of SI and possible problem triggers with regard to high-speed texts. Next, Peter Newmark’s classification of linguistic functions is introduced to provide a theoretical foundation for the division of primary and secondary information in the main body of this paper. At last, previous studies on the presentation and delivery speed of SI are summarized and insufficiencies pointed out so that we can draw lessons from them and explore new room for study.In the empirical part, this paper adopts David Rose’s speech at Ted as the testing material and has thirteen graduate students from the Graduate School of Translation and Interpretation who have learned SI for one semester tested and interviewed. To ensure the fullness of data collection, we choose students with different levels of language competency from different classrooms. Later, based on the experimental results, a quantitative analysis is made to figure out the quantity and frequency of primary and secondary information for each examinee, followed by a qualitative analysis that sums up the major problems triggers and delves thoroughly into each problem.This paper finds that the major problem triggers of key message extraction failure in SI lies in the way interpreters deal with secondary information. Among repetitive information, explanatory information and redundant beginnings, explanatory information proves to be the largest hindrance to interpreters’listening and analyzing. Since high-speed texts make it difficult for interpreters to tell primary information from secondary information, following the text too closely will only lead to fragmented production without any logic. Instead, the deliberate lengthening of EVS to facilitate active listening, omission, summary, and concise production are the best alternatives to extract the key message.