One morning ten years ago, when I was still an interpreting student, my fellow classmates and I came out from the simultaneous interpreting (SI) booths after a grueling practice session. The teacher, after pointing out all the faults we had made, nonchalantly ended the class by saying, “If you can’t anticipate what the speaker is going to say, you won’t be able to do SI. Start anticipating!” Ten years on, I often find myself silently reciting this exclamation before turning on the microphone on the interpreter’s console in the booth. I have also found myself relaying this mantra to my own interpreting students for the past several years.
However, how does an interpreter go about anticipating? What are the
processes involved? Are there neural correlates that could serve as hard evidence to show that interpreters are actually anticipating what the speaker is going to say?
Without looking into questions like these, it is quite difficult to figure out how one could teach anticipation to students, let alone tell them what to anticipate.
There is scant literature on anticipation in SI, and fewer instructions on how to teach anticipation or improve anticipation abilities. The biggest volume on
anticipation in interpreting studies is probably Ghelly Chernov’s work entitled
Inference and Anticipation in Simultaneous Interpreting: A Probability-Prediction Model, published in English in 2004.
1 His main argument was that SI is only possible because of an “objective redundancy” and a “subjective redundancy” in natural discourse. Objective redundancy refers to “theme” (i.e., repetitiveinformation) and “rheme” (i.e., new information) that are juxtaposed and alternated to
1 The original version was published in Russian in 1987 under the title Основы Синхронного Перевода (Introduction to Simultaneous Interpretation).
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form peaks and troughs in information density. Subjective redundancy refers to the interpreter’s familiarity with such parameters of the discourse situation as speaker, topical knowledge, and socio-pragmatic relationships. Therefore, if interpreters could analyze and discern between old and new segments of information, they could then focus their attention on dealing with the critical rheme while “compressing” (p.
113) the repetitive theme (Chernov, 2004). Most importantly, interpreters’ brains
“[generate] hypotheses in anticipation of certain verbal and semantic developments of the discourse” (p. 93). These hypotheses could be generated because there are
multiple levels of redundancy and a cyclical alternation between “theme” and “rheme”
as discourse unfolds, therefore leading to predictability (Chernov, 2004).
Chernov validated his theory by an experiment. He asked professional interpreters to interpret (simultaneously) two types of sentences: syntactically well-formed but semantically anomalous sentences such as “The round knife flew
squarely inside the bottom of smoke,” and sentences with misleading anticipatory cues
such as “Very often we are told that Rome was not built in a day. Of course werealize that Rome was not built in a dale.” The results validated his hypothesis:
interpreters could barely interpret the first kind, and there were many pauses, errors, and omissions in their renditions. In contrast, for the second type of sentences, despite the smooth translations, interpreters followed their own anticipation in 75% of all analyzable cases, meaning that they made the wrong rendition of the last
proposition because the sentences ended with unexpected words (Chernov, 2004).
However, these behavioral results do not reveal the actual process of hypothesis generation in the interpreters’ brains. Chernov’s exemplary theory of “message development probability anticipation” provided a description of the psycholinguistic mechanism which, in his views, made SI possible. Nonetheless, it would be potentially meaningful to actually see neural evidence that interpreters’ brains are
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indeed working to generate the said hypotheses, or simply put, that anticipation is taking place. It would be meaningful because if such neural evidence exists and we could compare and contrast the evidence of interpreting students with that of
professional interpreters, we could potentially trace and analyze the underlying processes of anticipation. This would give us a better understanding of whether anticipation is teachable, and advance the endeavors of developing ways to teach anticipation.
Seeking neural evidence inevitably implies that brain imaging techniques have to be employed. The use of event-related potentials (ERPs), an imaging technique that utilizes electroencephalography (EEG), is especially useful, because it has high temporal resolution, which would benefit studies focusing on language processing.
Although there have been a few ERP studies that have recruited professional
interpreters as subjects, none on the issue of anticipation per se has been carried out.
Naturally, the methodological challenges and attitudinal issues mentioned by Gile (1995) and Pöchhacker (2004) are valid reasons why neurolinguistic experiments in interpreting studies are so rare. Cognitive neuroscientists and psycholinguists are not necessarily interested in the kinds of phenomena interpreter-cum-researchers are excited about, while interpreters rarely possess the scientific and methodological know-how to perform experimental research that meet the criteria of the brain imaging community.
Therefore, the motivation of the present study is to lay down one additional brick to shorten the gap between interpreting studies and cognitive neuroscience. In the course of this undertaking, there are three objectives to meet.
Firstly, the present study hopes to find the neural correlates of language anticipation in interpreters.
Secondly, it has been suggested that expert interpreters are capable of predicting
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upcoming information so as to allocate mental resources to other processes (Liu, 2008). The present study hopes to explore whether there is neural evidence to support this conjecture, and whether novice interpreters perform differently.
Thirdly, the present study hopes to elucidate the sentence comprehension process of interpreters. Should neural evidence permit, it could provide a hint on how anticipation should be perceived or could be taught in the future.
To attain these goals, the present study will adopt and modify experiment paradigms used in previous ERP anticipation studies and recruit as subjects
interpreters of different levels of expertise. It is hypothesized that expert interpreters would show better anticipation abilities, and such advantage could be identified in neural correlates.
Chapter 2 provides a synopsis of past literature on interpreting expertise and anticipation studies using ERP. Chapter 3 describes the methods used in the present experiment. Chapter 4 summarizes the results of the experiment. Chapter 5 discusses the findings, and Chapter 6 is the conclusion.
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