Conference interpreters typically work in a simultaneous interpreting booth, where they listen to a speech in a source language and articulate a sequence of words with corresponding content in a target language. Written translation typically involves a text-to-text translation. Sight translation is a hybrid form which involves the reading of a text and the concomitant oral production of equivalent content in a target language. It is typically used when a document has to be accessed in an interpreter-mediated setting, for instance, minutes of a meeting, a letter from an absent person at a function, a medical report in a hospital, or a witness statement in a court (Čenková, Reference Čenková and Pöchhacker2015). It progresses from the visual perception of text to the production of speech, and with the advent of eye-tracking and speech-analysis technologies, it has become possible to observe—in real time and under relatively natural task conditions—the temporal dynamics of this task. The study aimed at investigating how sight translators coordinate the viewing of source-language text with the ensuing translation leading to the production of the target language text. Furthermore, we wanted to investigate whether interpreters’ decisions when to start producing the target language text (relative to the onset of source text reading) influence task performance. In other words, our goal was to test whether interpreters’ individual translation onset strategies influence sight translation.

To date, a relatively small number of studies have recorded eye movements during sight translation (Chmiel & Mazur, Reference Chmiel, Mazur, Way, Vandepitte, Meylaerts and Bartłomiejczyk2013; Dragsted & Hansen, Reference Dragsted and Hansen2009; Huang, Reference Huang2011; Jakobsen & Jensen, Reference Jakobsen, Jensen, Göpferich, Jacobsen and Mees2008; Korpal, Reference Korpal2012; McDonald & Carpenter, Reference McDonald and Carpenter1981; Shreve et al., Reference Shreve, Lacruz, Angelone, Shreve and Angelone2010). Some of them focused on structural reformulation (Chmiel & Lijewska, Reference Chmiel and Lijewska2019; Ma et al., Reference Ma, Li and Hsu2021) and syntactic cues (Ruiz & Macizo, Reference Ruiz and Macizo2019), while other focussed on processing patterns but without using both early and late eye-tracking measures (Su & Li, Reference Su and Li2020). Only one of them, McDonald and Carpenter’s (Reference McDonald and Carpenter1981) pioneering study, used a comprehensive set of measures to examine directly how the viewing of the source text is linked to the articulation of the corresponding content in a target language.

In McDonald and Carpenter’s study, four German–English bilinguals sight translated English passages into German. Each passage contained an ambiguous phrase (e.g., “kick the bucket”) that was preceded by context which primed either its literal or idiomatic meaning (i.e., “kicking an object” or “dying,” respectively). Moreover, the phrase was followed by a disambiguating sentence that indicated whether the literal or idiomatic meaning was to be assigned. An initially selected meaning for the ambiguous was thus confirmed, when priming and disambiguating contexts matched, or disconfirmed, when they mismatched. The viewing of an ambiguous phrase and its speech production were analyzed, and its viewing pattern was related to its corresponding speech production.

The analyses revealed three distinct viewing phases: initially, translators moved the eyes along a sequence of visible words, three to five words on average. The first phase was followed by a second one during which previously read text was re-viewed and during which the articulation of a corresponding translation occurred. When meaning selection was disconfirmed during the subsequent reading of the disambiguating sentence, translators often initiated a third phase. This phase consisted of an additional re-viewing of prior text and the articulation of a corrected translation.

Huang’s (Reference Huang2011) study appears to favor McDonald and Carpenter’s account according to which first-pass viewing during sight translation corresponds to first-pass viewing in reading for comprehension. In the study, eye movements of interpreting trainees were monitored in three tasks: the silent and oral reading of Chinese text and during Chinese-to-English sight translation. Huang’s analysis of word viewing durations showed that initial (first-pass) viewing durations were considerably shorter during silent than during oral reading (see also Inhoff & Radach, (Reference Inhoff and Radach2014). With oral reading, the articulation of visible words thus slowed primarily the first-pass progression through the text. In striking contrast to this, first-pass viewing during sight translation was similar to first-pass viewing during silent reading, but the translation task involved substantially more second-pass (and higher order) re-reading. Overall, Huang’s findings suggest that first-pass word viewing by interpreting trainees was equivalent during sight translation and silent reading for comprehension, and that translation of words and the corresponding articulation occurred during second (and later) pass viewing.

Although Huang’s task comparisons are consistent with McDonald and Carpenter’s processing account, the evidence must be considered tentative, as the evidence for a key assumption, that processing during the first-pass viewing is similar during silent reading and sight translation, entails an acceptance of the null hypothesis. Moreover, other influential studies suggest that translators extract some target language information early in the processing of to-be-translated visible words (de Groot, Reference de Groot1992; Ruiz et al., Reference Ruiz, Paredes, Macizo and Bajo2008).

In Ruiz et al.’s (Reference Ruiz, Paredes, Macizo and Bajo2008) study, professional translators were asked to sight translate Spanish to English sentences. These were displayed word-by-word, so that the presentation duration of each word was controlled by the translator through button pressing. Source-language sentences contained a member of a critical word pair that was matched on word frequency. It could occupy either the beginning or ending location in the sentence, and its corresponding English equivalent had either a high or a low frequency of occurrence. Two tasks were used: in one, the viewing of the final word of the Spanish sentence was followed by the articulation of an English translation; in the other, the viewing of the final word of the Spanish sentence was followed by a verbatim repetition of the sentence. With this approach, the word frequency of the to-be-articulated English (target language) word influenced the manually controlled presentation duration of the Spanish source word in the translation task when the target was at the end of the sentence, with a longer viewing time when the English translation of the source word had a low frequency of occurrence. The word frequency of the English translation had no effect when the critical source-language word was in the middle of the sentence and in the sentence repetition task. According to Ruiz et al. (Reference Ruiz, Paredes, Macizo and Bajo2008), these findings imply that the translation of the critical Spanish source word occurred while it was presented; otherwise, the frequency of the English translation could not have influenced the viewing of the Spanish source word.

In de Groot’s (Reference de Groot1992) single word processing study, Dutch–English bilinguals viewed individually presented high- or low-frequency Dutch words, and their task was either to articulate a word in English with equivalent meaning or to recognize its English translation. Both tasks showed that word frequency in the source and the target language, Dutch and English, respectively, influenced responding, which was faster and more accurate for high-frequency words in each language.

While these findings (de Groot Reference de Groot1992, Ruiz et al., Reference Ruiz, Paredes, Macizo and Bajo2008) indicate that the recognition of individual source words and the accessing of equivalent lexical forms into the target language occur while they are viewed, they do not provide a fine-grained account of the processing involved in sight translation. The study by Ruiz et al. (Reference Ruiz, Paredes, Macizo and Bajo2008) employed a self-paced reading paradigm, which made it impossible to distinguish between early and late stages of source-language processing. In the study by de Groot (Reference de Groot1992), the translation of visible words had to occur “on the spot,” that is, before the next word was shown, that is, task demands required that recognition and translation occurred while a word was viewed. The study measured response times only and provided no chance to see the distinction between the processes occurring during first-pass viewing and the subsequent re-viewing of a word. Unlike the studies by Ruiz et al. and de Groot, the current study offers a fine-grained analysis of reading in the sight translation task, thanks to the application of eye-tracking.

In turn, the motivation for the examination of the role of participants’ individual translation strategies in the current study came from Christoffels and de Groot (Reference Christoffels, Groot, Kroll and de Groot2005). They argued that the duration of the ear-voice span during simultaneous interpreting (i.e., the delay between hearing a source-language word and producing its translation equivalent) is determined by two competing strategies. One is to hear as much and to “wait as long as possible” (long wait) prior to translation, so that the intended meaning of the orally perceived language can be determined. The other is to “keep the lag as short as possible” (short wait) so that working memory will not be overloaded in this difficul task, and the risk of losing the thread of perceived speech is minimized. During sight translation, a long wait strategy could involve the reading of a relatively large number of words prior to translation, to minimize translation errors, and a short wait strategy could involve the reading of relatively few words prior to its translation, to simplify the translation task and to reduce working memory load.

The current study aimed at investigating the coordination of source text viewing and the articulation of translation equivalents. More specifically, sight translation performance was analyzed taking into consideration McDonald and Carpenter’s account of processing stages in sight translation. We also aimed to examine whether and how interpreters’ translation strategies (i.e., decisions when to start articulation of translation equivalents relative to the onset of text viewing) influenced the fluency and accuracy of their sight translation performance.

Our approach was similar to McDonald and Carpenter’s (Reference McDonald and Carpenter1981) study in that we recorded the viewing of to-be-translated text and the production of its spoken translation concurrently. The size of the tested population in the current study was considerably larger, however, and instead of using passages with ambiguous phrases, we used declarative sentences that contained unambiguous high- and low-frequency nouns in order to manipulate the ease of translation. Unlike in McDonald and Carpenter’s (Reference McDonald and Carpenter1981) study, we did not attempt to mislead translators about the meaning of to-be-translated phrases, and this was assumed to lead to the adoption of a more natural sight translation strategy. Prior work suggested that the translation of high-frequency words would be more accurate than the translation of low-frequency words (de Groot, Reference de Groot1992) and that professionals would translate target words and sentences more accurately than trainees (García et al., Reference García, Ibanez, Huepe, Houck, Michon, Lezama, Chadha and Rivera-Rei2014).

The frequency effect constitutes one of the most robust effects in psycholinguistics (Cop et al., Reference Cop, Keuleers, Drieghe and Duyck2015) and is considered to arise during initial stages of reading, that is, during lexical access. Eye movement research has shown that during intensive reading of sentences (or texts) frequency effects are especially pronounced in first-pass reading measures leading to longer first fixation durations, single fixation durations, gaze durations, or even go-past times on low-frequency words than on high-frequency ones (Inhoff & Rayner, Reference Inhoff and Rayner1986; Kliegl et al., Reference Kliegl, Grabner, Rolfs and Engbert2004; Rayner & Duffy, Reference Rayner and Duffy1986; Slattery et al., Reference Slattery, Pollatsek and Rayner2007; White, Reference White2008; but see Inhoff, Reference Inhoff1991). The typical finding is that a large frequency effect is found in tasks requiring careful reading, for example, during reading for comprehension (Radach et al., Reference Radach, Huestegge and Reilly2008) whereas tasks with less emphasis on careful reading (e.g., text scanning) yield reduced or no frequency effect at all (Schad et al., Reference Schad, Nuthmann and Engbert2012; White et al., Reference White, Warrington, McGowan and Paterson2015). Consequently, the frequency effect has been used as an index of the depth of lexical processing during various reading tasks (Schotter et al., Reference Schotter, Bicknell, Howard, Levy and Rayner2014; White et al., Reference White, Warrington, McGowan and Paterson2015). In order to gain insight into the nature of reading in sight translation, we measured the time spent viewing critical words during their initial encounter (i.e., during first pass, here indexed by first fixation duration, gaze duration, and go-past time) and when they were subsequently re-viewed (i.e., during second pass, here indexed by re-view duration and total viewing duration).

Our understanding, based on McDonald and Carpenter’s account, is that sight translation begins with first-pass reading that—on a word level—is similar to regular reading for comprehension activity performed by bilinguals. Words are identified and lexical access occurs. We know from previous research from psycholinguistics and translation studies that this lexical access is language nonselective, which means that same language synonyms and other language translation equivalents are co-activated (e.g., Lauro & Schwartz, Reference Lauro and Schwartz2017; Schaeffer & Carl, Reference Schaeffer and Carl2013; Titone et al., Reference Titone, Libben, Mercier, Whitford and Pivneva2011; Van Assche et al., Reference Van Assche, Brysbaert, Duyck, Heredia and Cieślicka2020; Whitford et al., Reference Whitford, Pivneva, Titone, Heredia, Altarriba and Cieślicka2016). This phase is followed by second and subsequent viewing passes, during which comprehension continues and translation occurs. This is where reading in sight translation differs from reading for comprehension. In the second and subsequent viewing passes, the reader integrates lexical information for a given word with the sentence. We believe that complex translation processes leading to the articulation of translation equivalents take place here (including further activation of appropriate translation equivalents, inhibition of inaccurate previously activated words, etc., i.e., these are processing components in which translation expertise offers an advantage). Thus, the first-pass viewing of words is similar in reading for sight translation and reading for comprehension and this similarity is observable only via eye-tracking and not in self-paced reading or reaction time experiments, wherein early and later stages of word processing cannot be easily distinguished.

If first-pass measures are similar in reading for sight translation and reading for comprehension (Huang, Reference Huang2011; McDonald & Carpenter, Reference McDonald and Carpenter1981), then first-pass viewing durations (i.e., first fixation duration, gaze duration, and go-past time) should be shorter for high- than for low-frequency targets, as occurred during monolinguals’ and bilinguals’ silent reading of text (Clifton et al., Reference Clifton, Ferreira, Henderson, Inhoff, Liversedge, Reichle and Schotter2016; Cop et al., Reference Cop, Keuleers, Drieghe and Duyck2015; Rayner, Reference Rayner1998, Reference Rayner2009; Whitford & Titone, Reference Whitford and Titone2014, Reference Whitford and Titone2015). Furthermore, if the initial phase of reading for comprehension and reading for sight translation is indeed similar, then translation expertise should not influence first-pass word viewing durations.

Further, the first-pass viewing of words should be followed by re-viewing in line with McDonald and Carpenter’s (Reference McDonald and Carpenter1981) account and prior findings by Huang (Reference Huang2011). While the effects of word frequency emerge primarily during first-pass viewing during silent reading (Kliegl et al., Reference Kliegl, Grabner, Rolfs and Engbert2004; Rayner & Duffy, Reference Rayner and Duffy1986; Slattery et al., Reference Slattery, Pollatsek and Rayner2007; White, Reference White2008), word frequency effects could be larger during the re-viewing (indexed by re-view duration and total viewing duration) than during the first-pass viewing (i.e., first fixation duration, gaze duration, and go-past time) in the sight translation task, as word frequency also influences processing that precedes articulation of translation equivalents. Moreover, translation expertise should influence re-viewing (i.e., re-view duration and total viewing duration), with shorter processing times for professionals than for trainees.

The concurrent recording of translators’ eye movements and of their spoken translation was used to determine their temporal (“wait”) strategy prior to translation onset. A relatively rapid onset of a spoken sentence translation after the presentation of a to-be-translated sentence (referred to as translation onset latency [TOL]Footnote ¹ ) was assumed to index an “early start” (or short wait) strategy. Conversely, looking at a sentence for a considerable amount of time prior to the onset of its translation was assumed to reveal a “late start” (long wait) strategy. In view of Christoffels and de Groot (Reference Christoffels, Groot, Kroll and de Groot2005), we assumed that translation strategy would influence translation performance, and that a long wait strategy (large TOLs) would generate more accurate sight translations. In addition, we expected that translation experts would prefer longer waits while trainees would prefer shorter waits.

Method

Participants

Twenty-four professional conference interpreters (13 females, 11 males) and 15 interpreting trainees (11 females, 4 males) participated in the study. The professionals, all active on the Polish market as freelance interpreters, were recruited through a translation agency. Their mean age was 38 (SD = 8.25), and their mean experience as conference interpreters ranged from 6 to 37 years with a mean of 13 years (SD = 8.00). The mean number of conference days (i.e., working days with the maximum of 6 hr of interpreting) per month in the 3 years preceding the study was 6 (SD = 4.37). Polish was their native language (L1) and English as their second language (L2); several were also proficient in other languages (L3s included Russian, French, German, and Italian). Their mean LexTALE score (Lemhöfer & Broersma, Reference Lemhöfer and Broersma2012) for English was 89.31 (SD = 9.31). The trainees’ mean age was 23 (SD = 0.91). All had Polish as their L1 and English as their L2 (CEFR, Council of Europe (2001) level C1 or C2); some had L3s (German, French, Spanish, or Chinese). The trainees were familiar with strategies of sight translation which they performed during classes. All trainees were at the same stage, that is, halfway through the second semester of their four-semester conference interpreting programme and none had any professional interpreting experience. Before the experiment, all participants reported no history of hearing or neurological problems, and all of them had normal or corrected-to-normal vision. No approval from the Ethics Committee was necessary for this study. As the participants performed a sight translation task in the study, we refer to them as translators rather than interpreters in the present paper.

Apparatus

An Eye-Link 1000 Plus with a desktop mount was used to record eye movements in remote mode. The sampling rate was 500 Hz (SR-Research, Ontario, Canada). Viewing was binocular, but eye movements were recorded from the right eye only. Sentences were presented on a 21-inch LSD monitor, positioned approximately 60 cm from participants. Sentences were presented in black, 14-point Courier New font (ensuring equidistant character spacing) on a white background using Experiment Builder software (SR-Research, Ontario, Canada). Eye movements were calibrated with a 13-point grid. Speech was recorded throughout a trial with a Philips microphone and recorded input was analyzed with Audacity(R) recording and editing software (Audacity Team, 2017). Translation accuracy was determined offline by a professional translator.

Materials

The critical words in the to-be-translated English sentences were 30 high-frequency nouns and 30 paired low-frequency nouns. The processing of these words was of primary interest. The two members of a critical word pair were matched for length and concreteness, and their meaning was congruent with a constructed sentence frame. The frequency data for these critical words were taken from SUBTLEX-UK (van Heuven et al., Reference van Heuven, Mandera, Keuleers and Brysbaert2014) and concreteness ratings from the Brysbaert, Warriner and Kuperman (Reference Brysbaert, Warriner and Kuperman2014) database. Frequency data for the Polish equivalents were taken from SUBTLEX-PL (Mandera et al., Reference Mandera, Keuleers, Wodniecka and Brysbaert2014). Concreteness ratings for corresponding Polish translations were not available but are not likely to significantly differ from the ratings in English. Of the 60 critical English nouns, none had a Polish cognate. Table 1 shows characteristics of the critical source-language words and their Polish equivalents. Thirty sentences frames were constructed that could accommodate the high- and the low-frequency member of a critical word pair. Also, care was taken to retain a relatively consistent syntactic structure across sentences. Each participant saw only one of the two lists.

Table 1. Characteristics of English stimulus words and their Polish equivalents. Frequency counts are shown as mean Zipf scores, word length is given in the number of characters, and concreteness was estimated on a 5-point Likert scale (standard deviations in parentheses)

To reduce the skipping (nonfixation) of critical words, they were preceded by a word with at least six letters (Rayner, Reference Rayner1998). Table 2 shows only samples of the experimental materials and the full list of stimuli is given in Supplementary Material. A MANOVA that compared frequency and length across languages revealed no significant difference in length between the critical English source words and their Polish translation in the high- and low-frequency condition (p > .05). The frequency manipulation, by contrast, yielded a significant difference between high- and low-frequency words in both languages (p < .001).

Table 2. Sample experimental stimuli (targets in capitals)

The predictability of critical source-language words was determined via a cloze test that was distributed online to 27 evaluators who were native speakers of Polish with English as their L2 at the proficiency level (C1 or C2 according to CEFR, Council of Europe, 2001). They read the English sentence frames (without target words) and filled in fitting English words. If over 30% of respondents completed a sentence frame with the same word, the sentence was removed from the stimulus set. As a result of the first round of norming, five sentences were removed. Modified versions were normed in a second round by 35 evaluators (coming from the same population as the first group of evaluators). The mean cloze value of high- and low-frequency source words was 2.7% and 0%, respectively, indicating that none of the targets was constrained by prior context. Increases in the frequency of a target word were, however, associated with increases in the number of its acceptable English-to-Polish translations. Specifically, we calculated critical source words’ translation entropy (HTra) (Carl & Schaeffer, Reference Carl and Schaeffer2017), defined as the number of “choices a translator has for a given source text word, that is how many equally likely translations may be produced in a given context” (Schaeffer et al., Reference Schaeffer, Dragsted, Hvelplund, Balling, Carl, Carl, Bangalore and Schaeffer2016, p. 185). The entropy values of high- and low-frequency words were 0.77 and 0.49, respectively, and the correlation between HTra values and target frequency was r = .27, across items (t = 2.17, df = 58, p < .05). Together these examinations indicate that high-frequency source words should have a general recognition and translation advantage, their recognition and translation being easier than the recognition and translation of low-frequency source words.

The materials also included 62 filler sentences so that participants would not encounter difficult words that were relatively difficult to identify and to translate on a large proportion of trials. Two lists of sentences were constructed. Each list contained the same 30 sentence frames with a different member of the critical word pair. Half the critical source words on a list were low-frequency words and the remaining critical source words were high-frequency words. Both lists also contained the identical set of filler sentences. The experimental sentences were displayed in no more than two lines of text. Importantly, the target word never occupied the beginning or ending two word locations on the screen.

Procedure

The experiment was designed using the Experiment Builder (SR-Research) program. A session started with the sight translation of 10 practice sentences, and this was followed by the translation of one list of sentences.

To record eye movements, participants faced the eye-tracker and the computer screen. We used the eye-tracker in remote mode, which meant that the participants put a target sticker on their foreheads and performed a 13-point calibration. A recalibration was performed between trials as needed. An obligatory recalibration was performed half-way through the experimental block (after 46 sentences).

Trials began with a fixation point (black dot) displayed where the first letter of the sentence later appeared. The participants were instructed to sight translate the English sentence appearing on the screen into Polish. They were told that the usual time constraints of professional sight translation should be applied. This meant that translators should perform the translation task as fast as possible. When the participant finished the spoken translation of a visible sentence, the experimenter initiated the presentation of the next sentence (or initiated a calibration if needed). The session lasted approximately 25 min. On each trial, eye movements were recorded from the onset of a sentence until its visibility was terminated, and production of a translation was recorded from the onset of a visible sentence to the end of articulation.

Data analysis

Two sets of analyses were applied. The analysis of the viewing of critical words allowed us to investigate whether comprehension and translation are serial or co-occur during sight translation. In turn, the analysis of the quality of translation performance examined the role of participant’s individual decisions of when to start translation production relative to the onset of reading (through TOL) during sight translation. All statistical analyses were performed with the R system for statistical computing (R Core Team, 2020). Linear mixed models and generalized linear mixed models, as implemented in the lme4 library (Bates et al., Reference Bates, Mächler, Bolker and Walker2015), were used for the analyses of trial-based numeric and binary data, respectively. A linear mixed model from library ordinal (Christensen, Reference Christensen2019) was used to analyze sentence accuracy ratings.

The following fixed effect structure was applied to the set of critical word viewing data. Critical word frequency, translation expertise, and the interaction of the two factors were used as fixed effects, as this sufficed for the testing of the serial processing and the co-occurrence hypothesis.

The fixed effects for the larger set of translation performance data (sentence accuracy, critical word accuracy, and cumulated pause duration) were critical word frequency (high vs. low), translation expertise (professional vs. trainee), and a linear trend for the wait strategy (TOL). Since exploratory analyses suggested that short and long TOLs could be associated with higher-quality translations, the model also included a quadratic trend for TOL. In addition, the model included fixed effects for the interaction of critical word frequency with expertise and the linear and quadratic TOL trends. Sum contrasts were applied to the factors frequency and expertise, so that effect sizes reflected the distance of a condition from the grand mean. The numeric TOL values were centered.

The binary values of the factor expertise were slightly correlated with the linear component of TOL (r = .21) but not with the quadratic component (r = −.07). Nevertheless, statistical models with these fixed effects examined potential effects of collinearity with Anova models with type 3 sums of squares. For sentence translation accuracy, we applied the Anova.clmm function from library RVAideMemoire (Hervé, Reference Hervé2021), and for all other models, we applied the Anova function from library car (Fox & Weisberg, Reference Fox and Weisberg2010).

At the outset, all linear mixed models used a maximal random factor structure with random intercepts for participants and items, and random slopes for critical word frequency. Since each sentence frame contained low- and high-frequency critical words and was read by professionals and trainees, the random factor structure for items also included random slopes for expertise and the interaction of expertise with word frequency. In addition, the maximal model included the correlations of random factor components. Application of a random factor principal component analysis (with the rePCA function), as suggested by Matuschek et al. (Reference Matuschek, Kliegl, Vasishth, Baayen and Bates2017), indicated that the maximal random factor structure yielded an over-parameterized fit for most statistical models. When this was the case, we followed Matuschek et al. and used a “top-down” approach to simplify the model. In a first step, we removed all random factor correlations, and when this did not eliminate random factor over-parameterization, the random factor component with the smallest amount of variance was dropped from the model until overfitting was eliminated. Across simplified models, this yielded a random factor structure with four to six components.

The frequency distributions of the to-be-analyzed numeric measures deviated from the normal distribution. Specifically, the skewing of pause durations and of the five critical word viewing duration measures was positive. In a first step, these data sets were log transformed which yielded close-to-normal distributions for all five viewing duration measures except total viewing durations. A square root transformation yielded close-to-normal frequency distributions for this measure and also for pause durations. The reported coefficients of the statistical models are thus based on the ordinal (ranked) values for sentence translation accuracy ratings, on logits for critical word translation accuracies, on square root transformed values for pause durations and total viewing durations, and on log transformed first fixation durations, gaze durations, go-past times, and re-reading durations. Figures and tables show backtransformed condition means and standard errors that were extracted from statistical models with function emmeans from library emmeans (Lenth et al., Reference Lenth, Singmann, Love, Buerkner and Herve2020). Figure 1 was plotted with ggplot2 (Wickham, Reference Wickham2016).

Figure 1. Critical word accuracy (upper panel) and pause duration (lower panel) with the corresponding standard error as a function of wait strategy (TOL) and target frequency. Sentence-specific TOL values were grouped into five bins of approximately equal size that corresponded to very short, short, average, long, and very long waits prior to translation onset. Standard errors were computed for each bin.

Results

Critical word viewing

In order to determine the nature of reading in sight translation, we analyzed word viewing measures as a function of target word frequency and translation expertise. The means and standard errors for the five critical word viewing measures are shown in Table 3 as a function of word frequency and expertise.

Table 3. Means and standard errors (in parentheses) for measures of critical word viewing, re-reading, and translation quality as a function of word frequency and expertise

All five measures showed numerically shorter viewing durations for the high-frequency condition. However, the word frequency effect was not significant for first fixation duration, which yielded a relatively small numeric difference, 9 ms (b = −0.018, SE = 0.020, t = −0.884, p = .347). The frequency effect was larger, 43 ms, for gaze durations (b = −0.063, SE = 0.027, t = −2.308, p = .05) and increased to 100 ms for go-past times (b = −0.092, SE = 0.043, t = −2.159, p < .05). Importantly, the effect of expertise was negligible across these three viewing measures, amounting to 6 ms shorter first fixation durations for experts (b = −0.011, SE = 0.029, t = −0.375, p = .710), 2.5 ms longer gaze durations (b = 0.013, SE = 0.036, t = 0.361, p = .720), and 94 ms longer go-past times for experts than for trainees (b = 0.090, SE = 0.072, t = 1.239, p = .222). The interaction of the two main effects was negligible across the three measures (all p > .30). Together, all three show familiar benefits for high-frequency words, and none of them revealed shorter critical word viewing durations for professional interpreters; hence, no effect of expertise was found.

Re-reading durations and total viewing durations (which include re-reading time) showed, by contrast, reliable effects of expertise. The re-reading durations of professionals were 213 ms shorter than the re-reading durations of trainees (b = −0.102, SE = 0.043, t = −2.370, p < .025). The corresponding benefit of expertise amounted to 186 ms for total viewing durations (b = 0.078, SE = 0.038, t = 2.056, p < .05). Although the numeric differences between groups were larger for low-frequency words, the interaction of the two main effects did not approach significance (both p > .12).

The means and standard errors for the three types of critical word re-reading are shown in Table 3. In it, regressions out of a critical word (so that it is re-read with a forward-directed saccade) are labeled Out-Regressions and backward directed regressions to the critical word are labeled In-Regressions. Instances in which both types of regressions occurred are labeled In+Out-Regressions. As can be seen, re-reading with a regression back to a critical word (In-Regressions) was more common (50.3%) than re-reading after a regression out of a critical word (17.5%). Both types of re-reading occurred on 24% of the critical word viewing trials. Across the three measures, none of the fixed effects approached significance (all p > 0.176).

Together, these analyses show group-specific differences, as translation expertise influenced primarily the time spent re-reading critical words. Both groups accomplished re-reading primarily through regressions that were directed back to critical words, and there were no significant differences in their types of re-reading. Translation expertise thus influenced the time spent on the re-reviewing of words but not the programming of re-reading saccades and not the first-pass viewing.

Translation quality

In order to investigate how the participants’ wait strategies affected their performance in sight translation, we analyzed translation quality by looking into three measures: sentence accuracy, critical word accuracy, and cumulated pause duration (as a function of TOL coupled with word frequency and expertise).

The effects of wait strategy (TOL) on critical word translation accuracy and on pause durations are shown in Figure 1. Furthermore, Table 3 shows critical word translation accuracy, sentence translation accuracy, and pause duration as a function of word frequency and translation expertise.

The analyses of all three translation quality measures yielded a robust effect of critical word frequency, its translations being more accurate and more fluent in the high- than the low-frequency condition (an ordering effect of 0.51 for sentence translation accuracy: b = 0.258, SE = 0.095, z = −2.706, p < .01; a 27% higher critical word translation accuracy: b = −1.653, SE = 0.246, z = −6.707, p < .001; and 1.0 s shorter pause durations: b = −0.125, SE = 0.024, t = −5.047, p < .001). The main effect of translation expertise was also highly significant, professionals generating more accurate sentence translations, with an order effect of 1.25, a 23% higher critical word translation accuracy, and 1.09 s shorter pauses pause durations (b = 0.617, SE = 0.152, z = 4.046, p < .005; b = 0.543, SE = 0.224, z = 2.432, p < .05; and b = −0.1374, SE = 0.068, t = −2.028, p < .05, respectively). Most importantly, the linear effect of TOL was significant for critical word accuracy (b = 0.732, SE = 0.338, z = 2.169 p < .05), the translation of critical words being more accurate with longer TOLs (top panel of Figure 1). Furthermore, TOLs yielded a significant quadratic effect for pause duration (b = −0.101, SE = 0.048, t = −2.122, p < .05), as pauses were shorter when TOLs were either relatively short or long (bottom panel of Figure 1). No other effect approached statistical significance (all p > .196).

Together, the analyses of translation performance yielded familiar effects of word frequency and expertise. Translation was more accurate and more fluent in the high- than the low-frequency condition, and professionals translated more accurately and more fluently than trainees. Most importantly, there was also a relationship between participants’ TOL and performance. Critical word translations were more accurate with longer TOLs, and translation was more fluent when TOLs were short or long.