This corpus-based study explores the effects of relay interpreting at meetings of the United Nations General Assembly by comparing features of disfluency between the outputs of relay and non-relay simultaneous interpreting (SI). The findings are as follows: (1) the output of relay interpreting is shorter and more dispersive than that of non-relay interpreting; (2) filled pauses are the most common type of disfluency; and (3) the relay SI output shows fewer lexical and phonetic E-repairs and more A-repairs for ambiguity, syntactic E-repairs, and D-repairs than the non-relay output. The results suggest that the use of relay vs. non-relay interpreting may affect interpreters’ output.

Although simultaneous interpreting (SI) is generally recognized as a highly demanding cognitive activity in nature, the role of cognitive processes in SI fluency is yet to be determined. While utterance fluency refers to the set of objectively determined oral features of utterances, cognitive fluency means the speaker’s efficient mobilization and integration of underlying cognitive processes responsible for utterance production. An investigation into the relationship of the two dimensions of fluency helps to reveal the cognitive bases of interpreting. This study explores the predicting power of cognitive fluency in the utterance fluency development of L2 (English)–L1 (Chinese) SI output of trainee interpreters. Cognitive fluency was operationalized as measures of lexical access, linguistic attention control, and working memory capacity. Measures of utterance fluency were obtained through simulated SI tasks under conditions of low and high input rates. Twenty-eight trainees interpreted two speeches, one with a high input rate and the other with a low input rate, at the beginning and end of an SI training period of 13 weeks. A bilingual corpus of the participants’ SI output was built, and indicators of SI utterance fluency were annotated systematically. Utterance fluency was indexed by the speech rate, mean length of run, phonation time ratio, mean number of silent pauses, and mean number of disfluencies. Results of analyses indicated that (1) the predicting power of cognitive fluency for SI utterance fluency development was only shown under high cognitive load over a training period of 13 weeks; (2) predictors for the development of SI utterance fluency tended to be the efficiency of cognitive processes involved in the target language production stage; and (3) the inclusion of measures of working memory capacity significantly increased the predicting power of cognitive fluency for SI utterance fluency development. This study for the first time provides evidence for the role of cognitive fluency in trainee interpreters’ SI utterance fluency development, having implications for the theoretical framework of cognitive fluency and the information processing mechanism in interpreting process, as well as for interpreter aptitude tests and interpreting pedagogy.

Purpose: To evaluate the image quality of intraocular lenses (IOLs) using field-tracing optical simulation and then compare it with the image quality using conventional ray-tracing simulation. Methods: We simulated aspheric IOLs with a decenter, tilt, and no misalignment using an aspheric corneal eye model with a positive spherical aberration. The retinal image, Strehl ratio, and modulation transfer function (MTF) were compared between the ray-tracing and field-tracing optical simulation and confirmed by the results reported in an in vitro experiment using the same eye model. Results: The retinal image showed interference fringes from target due to diffraction from the object in a field-tracing simulation. When compared with the experimental results, the field tracing represented the experimental results more precisely than ray tracing after passing over 400 µm of the decentration and 4 degrees of the tilt of the IOLs. The MTF values showed similar results for the case of no IOL misalignment in both the field tracing and ray tracing. In the case of the 200-µm decentration or 8-degree tilt of IOL, the field-traced MTF shows lower values than the ray-traced one. Conclusions: The field-tracing optical bench simulation is a reliable method to evaluate IOL performance according to the IOL misalignment. It can provide retinal image quality close to real by taking into account the wave nature of light, interference and diffraction to explain to patients having the IOL misalignment.

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