The distractor frequency effect in picture–word interference: evidence for response exclusion

In 3 experiments, subjects named pictures with low- or high-frequency superimposed distractor words. In a 1st experiment, we replicated the finding that low-frequency words induce more interference in picture naming than high-frequency words (i.e., distractor frequency effect; Miozzo & Caramazza, 2003). According to the response exclusion hypothesis, this effect has its origin at a postlexical stage and is related to a response buffer. The account predicts that the distractor frequency effect should only be present when a response to the word enters the response buffer. This was tested by masking the distractor (Experiment 2) and by presenting it at various time points before stimulus onset (Experiment 3). Results supported the hypothesis by showing that the effect was only present when distractors were visible, and if they were presented in close proximity to the target picture. These results have implications for the models of lexical access and for the tasks that can be used to study this process

On the automaticity of language processing

People speak and listen to language all the time. Given this high frequency of use, it is often suggested that at least some aspects of language processing are highly overlearned and therefore occur “automatically”. Here we critically examine this suggestion. We first sketch a framework that views automaticity as a set of interrelated features of mental processes and a matter of degree rather than a single feature that is all-or-none. We then apply this framework to language processing. To do so, we carve up the processes involved in language use according to (a) whether language processing takes place in monologue or dialogue, (b) whether the individual is comprehending or producing language, (c) whether the spoken or written modality is used, and (d) the linguistic processing level at which they occur, that is, phonology, the lexicon, syntax, or conceptual processes. This exercise suggests that while conceptual processes are relatively non-automatic (as is usually assumed), there is also considerable evidence that syntactic and lexical lower-level processes are not fully automatic. We close by discussing entrenchment as a set of mechanisms underlying automatization

Speech monitoring and phonologically-mediated eye gaze in language perception and production: a comparison using printed word eye-tracking

The Perceptual Loop Theory of speech monitoring assumes that speakers routinely inspect their inner speech. In contrast, Huettig and Hartsuiker (2010) observed that listening to one's own speech during language production drives eye-movements to phonologically related printed words with a similar time-course as listening to someone else's speech does in speech perception experiments. This suggests that speakers use their speech perception system to listen to their own overt speech, but not to their inner speech. However, a direct comparison between production and perception with the same stimuli and participants is lacking so far. The current printed word eye-tracking experiment therefore used a within-subjects design, combining production and perception. Displays showed four words, of which one, the target, either had to be named or was presented auditorily. Accompanying words were phonologically related, semantically related, or unrelated to the target. There were small increases in looks to phonological competitors with a similar time-course in both production and perception. Phonological effects in perception however lasted longer and had a much larger magnitude. We conjecture that this difference is related to a difference in predictability of one's own and someone else's speech, which in turn has consequences for lexical competition in other-perception and possibly suppression of activation in self-perception

Phonological recoding in error detection: a cross-sectional study in beginning readers of Dutch

The present cross-sectional study investigated the development of phonological recoding in beginning readers of Dutch, using a proofreading task with pseudohomophones and control misspellings. In Experiment 1, children in grades 1 to 3 rejected fewer pseudohomophones (e. g., wein, sounding like wijn 'wine') as spelling errors than control misspellings (e. g., wijg). The size of this pseudohomophone effect was larger in grade 1 than in grade 2 and did not differ between grades 2 and 3. In Experiment 2, we replicated the pseudohomophone effect in beginning readers and we tested how orthographic knowledge may modulate this effect. Children in grades 2 to 4 again detected fewer pseudohomophones than control misspellings and this effect decreased between grades 2 and 3 and between grades 3 and 4. The magnitude of the pseudohomophone effect was modulated by the development of orthographic knowledge: its magnitude decreased much more between grades 2 and 3 for more advanced spellers, than for less advanced spellers. The persistence of the pseudohomophone effect across all grades illustrates the importance of phonological recoding in Dutch readers. At the same time, the decreasing pseudohomophone effect across grades indicates the increasing influence of orthographic knowledge as reading develops

Translation methods and experience : a comparative analysis of human translation and post-editing with students and professional translators

While the benefits of using post-editing for technical texts have been more or less acknowledged, it remains unclear whether post-editing is a viable alternative to human translation for more general text types. In addition, we need a better understanding of both translation methods and how they are performed by students as well as professionals, so that pitfalls can be determined and translator training can be adapted accordingly. In this article, we aim to get a better understanding of the differences between human translation and post-editing for newspaper articles. Processes were registered by means of eye tracking and keystroke logging, which allows us to study translation speed, cognitive load, and the usage of external resources. We also look at the final quality of the product as well as translators' attitude towards both methods of translation

Identifying the machine translation error types with the greatest impact on post-editing effort

Translation Environment Tools make translators' work easier by providing them with term lists, translation memories and machine translation output. Ideally, such tools automatically predict whether it is more effortful to post-edit than to translate from scratch, and determine whether or not to provide translators with machine translation output. Current machine translation quality estimation systems heavily rely on automatic metrics, even though they do not accurately capture actual post-editing effort. In addition, these systems do not take translator experience into account, even though novices' translation processes are different from those of professional translators. In this paper, we report on the impact of machine translation errors on various types of post-editing effort indicators, for professional translators as well as student translators. We compare the impact of MT quality on a product effort indicator (HTER) with that on various process effort indicators. The translation and post-editing process of student translators and professional translators was logged with a combination of keystroke logging and eye-tracking, and the MT output was analyzed with a fine-grained translation quality assessment approach. We find that most post-editing effort indicators (product as well as process) are influenced by machine translation quality, but that different error types affect different post-editing effort indicators, confirming that a more fine-grained MT quality analysis is needed to correctly estimate actual post-editing effort. Coherence, meaning shifts, and structural issues are shown to be good indicators of post-editing effort. The additional impact of experience on these interactions between MT quality and post-editing effort is smaller than expected

The impact of machine translation error types on post-editing effort indicators

In this paper, we report on a post-editing study for general text types from English into Dutch conducted with master's students of translation. We used a fine-grained machine translation (MT) quality assessment method with error weights that correspond to severity levels and are related to cognitive load. Linear mixed effects models are applied to analyze the impact of MT quality on potential post-editing effort indicators. The impact of MT quality is evaluated on three different levels, each with an increasing granularity. We find that MT quality is a significant predictor of all different types of post-editing effort indicators and that different types of MT errors predict different post-editing effort indicators