Translators’ Use of Digital Resources During Translation

HERMES - Journal of Language and Communication in Business ◽

10.7146/hjlcb.v0i56.97205 ◽

2017 ◽

pp. 71 ◽

Cited By ~ 2

Author(s):

Kristian Tangsgaard Hvelplund

Keyword(s):

Eye Movements ◽

Eye Tracking ◽

Cognitive Load ◽

Tracking Data ◽

Translation Process ◽

Digital Resources ◽

Use Of Resources ◽

Digital Resource

This paper presents the findings from a study on translators’ use of digital resources during the translation process. Eye tracking data and screen recording data from 18 professional translators are analysed in order to 1) examine how much time translators spend on digital resource consultation compared with translation drafting and translation revision, 2) examine how eye movements differ between translation drafting, revision and digital resource consultation and 3) investigate what types of digital resources are used by translators. The findings demonstrate that digital resource consultation constitutes a considerable amount of the translation process. The findings also show longer fixations and larger pupils during resource consultation, indicating heavier cognitive load, and finally the study identifies considerable variation in the use of resources between translators.

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A cognitive load delays predictive eye movements similarly during L1 and L2 comprehension

Bilingualism Language and Cognition ◽

10.1017/s1366728917000050 ◽

2017 ◽

Vol 21 (2) ◽

pp. 251-264 ◽

Cited By ~ 19

Author(s):

AINE ITO ◽

MARTIN CORLEY ◽

MARTIN J. PICKERING

Keyword(s):

Working Memory ◽

Eye Movements ◽

Eye Tracking ◽

Cognitive Load ◽

Memory Task ◽

Target Object ◽

Cognitive Resources ◽

Visual World ◽

L1 And L2

We used the visual world eye-tracking paradigm to investigate the effects of cognitive load on predictive eye movements in L1 (Experiment 1) and L2 (Experiment 2) speakers. Participants listened to sentences whose verb was predictive or non-predictive towards one of four objects they were viewing. They then clicked on a mentioned object. Half the participants additionally performed a working memory task of remembering words. Both L1 and L2 speakers looked more at the target object predictively in predictable- than in non-predictable sentences when they performed the listen-and-click task only. However, this predictability effect was delayed in those who performed the concurrent memory task. This pattern of results was similar in L1 and L2 speakers. L1 and L2 speakers make predictions, but cognitive resources are required for making predictive eye movements. The findings are compatible with the claim that L2 speakers use the same mechanisms as L1 speakers to make predictions.

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Spontaneous eye-movements during eyes-open rest reduce resting-state-network modularity by increasing visual-sensorimotor connectivity

Network Neuroscience ◽

10.1162/netn_a_00186 ◽

2021 ◽

pp. 1-39

Author(s):

Cemal Koba ◽

Giuseppe Notaro ◽

Sandra Tamm ◽

Gustav Nilsonne ◽

Uri Hasson

Keyword(s):

Eye Movements ◽

Eye Tracking ◽

Resting State ◽

Movement Control ◽

Clustering Coefficient ◽

Tracking Data ◽

Planar Imaging ◽

Experimental Conditions ◽

Sensory Motor ◽

Eyes Open

During wakeful rest, individuals make small eye movements during fixation. We examined how these endogenously-driven oculomotor patterns impact topography and topology of functional brain networks. We used a dataset consisting of eyes-open resting-state (RS) fMRI data with simultaneous eye-tracking (Nilsonne et al., 2016). The eye-tracking data indicated minor movements during rest, which correlated modestly with RS BOLD data. However, eye-tracking data correlated well with echo-planar imaging time series sampled from the area of the Eye-Orbit (EO-EPI), which is a signal previously used to identify eye movements during exogenous saccades and movie viewing. Further analyses showed that EO-EPI data were correlated with activity in an extensive motor and sensory-motor network, including components of the dorsal attention network and the frontal eye fields. Partialling out variance related to EO-EPI from RS data reduced connectivity, primarily between sensory-motor and visual areas. It also produced networks with higher modularity, lower mean connectivity strength, and lower mean clustering coefficient. Our results highlight new aspects of endogenous eye movement control during wakeful rest. They show that oculomotor-related contributions form an important component of RS network topology, and that those should be considered in interpreting differences in network structure between populations, or as a function of different experimental conditions.

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Reading patterns and cognitive processing in an eye-tracking study of note-reading in consecutive interpreting

Interpreting ◽

10.1075/intp.00050.che ◽

2020 ◽

Author(s):

Sijia Chen ◽

Jan-Louis Kruger ◽

Stephen Doherty

Keyword(s):

Eye Tracking ◽

Phase I ◽

Cognitive Load ◽

Cognitive Processing ◽

Phase Ii ◽

Preliminary Evidence ◽

Tracking Data ◽

Note Reading ◽

Reading Patterns ◽

Consecutive Interpreting

Abstract This article reports on the eye-tracking data collected from 18 professional interpreters while they performed consecutive interpreting with notes. It is a pioneering study in its visualisation of the way in which note-reading occurs. Preliminary evidence suggests that note-reading proceeds in a nonlinear manner. The data collected in this study also report on indicators of cognitive processing in consecutive interpreting, particularly during note-reading, which appears to be a cognitively demanding process. It differs from reading for comprehension in various ways, while staying closer to reading in sight translation. In addition, the data show that the note-taking choices made during Phase I of consecutive interpreting, in which interpreters listen to the source speech and write notes, affect the level of cognitive load in Phase II, in which interpreters read back their notes and produce a target speech.

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Spontaneous eye-movements during eyes-open rest reduce resting-state-network modularity by increasing visual-sensorimotor connectivity

10.1101/2020.05.18.100669 ◽

2020 ◽

Author(s):

Cemal Koba ◽

Giuseppe Notaro ◽

Sandra Tamm ◽

Gustav Nilsonne ◽

Uri Hasson

Keyword(s):

Eye Movements ◽

Eye Tracking ◽

Resting State ◽

Movement Control ◽

Clustering Coefficient ◽

Tracking Data ◽

Planar Imaging ◽

Experimental Conditions ◽

Sensory Motor ◽

Eyes Open

ABSTRACTDuring wakeful rest, individuals make small eye movements when asked to fixate. We examined how these endogenously-driven oculomotor patterns impact topography and topology of functional brain networks. We used a dataset consisting of eyes-open resting-state (RS) fMRI data with simultaneous eye-tracking (Nilsonne et al., 2016). The eye-tracking data indicated minor movements during rest, on the order of 1.0 degree on average when analyzed over 2sec epochs, which correlated modestly with RS BOLD data. However, the eye-tracking data correlated well with echo-planar imaging (EPI) time series sampled from the area of the Eye-Orbit (EO-EPI), which is a signal previously used to identify eye movements during exogenous saccades and movie viewing. We found that EO-EPI data correlated with activity in an extensive motor and sensory-motor network, but also some components of the dorsal attention network including the frontal and supplementary eye fields. Partialling out variance related to EO-EPI from RS data reduced connectivity, primarily between sensory-motor and visual areas. For three different network sparsity levels, the resulting RS connectivity networks showed higher modularity, lower mean connectivity strength, and lower mean clustering coefficient. Our results highlight new aspects of endogenous eye movement control during wakeful rest. They show that oculomotor-related contributions form an important component of RS network topology, and that those should be considered in interpreting differences in network structure between populations, or as a function of different experimental conditions.

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TO THE QUESTION OF PECULIARITIES OF EYE MOVEMENT ANALYSIS IN THE PROCESS OF FACE PERCEPTION

Moscow University Psychology Bulletin ◽

10.11621/vsp.2021.01.08 ◽

2021 ◽

pp. 196-219

Author(s):

Galina Ya. Menshikova ◽

Anna O. Pichugina

Keyword(s):

Eye Movements ◽

Eye Tracking ◽

Eye Movement ◽

Face Perception ◽

Dwell Time ◽

Holistic Processing ◽

Facial Features ◽

Tracking Data ◽

Individual Strategies ◽

Areas Of Interest

Background. The article is devoted to the study of the mechanisms of face perception when using the technology of eye-tracking. In the scientific literature, two processes are distinguished - analytical (perception of individual facial features) and holistic (perception of a general configuration of facial features). It is assumed that each of the mechanisms can be specifically manifested in patterns of eye movements during face perception. However, there is disagreement among the authors concerning the eye movements patterns which reflect the dominance of the holistic or analytic processing. We hypothesized that the contradictions in the interpretation of eye movement indicators in the studies of face perception may be associated with the features of the eye-tracker data processing, namely, with the specifics of identifying areas of interest (eyes, nose, bridge of the nose, lips), as well as with individual strategies of eye movements. Objective. Revealing the features of eye movements analysis in the process of facial perception. Method. A method for studying analytical and holistic processing in the task of assessing the attractiveness of upright and inverted faces using eye-tracking technology has been developed and tested. The eye-tracking data were analyzed for the entire sample using three types of processing, differing in the marking of the areas of interest (AOIs), and separately for two groups differing in eye movement strategies. The distinction of strategies was considered based on differences in the mean values of the fixation duration and the amplitude of saccades. Results. It was shown that: the presence of statistically significant differences of the dwell time in the AOIs between the condition of upright and inverted faces depended on the method of identifying these AOIs. It was shown that the distribution of the dwell time by zones is closely related to individual strategies of eye movements. Analysis of the data separately by groups showed significant differences in the distribution of the dwell time in the AOIs. Conclusion. When processing eye-tracking data obtained in the studies of face perception, it is necessary to consider individual strategies of eye movements, as well as the features associated with identifying AOIs. The absence of a single standard for identifying these areas can be the reason for inconsistency of the data about the holistic or analytical processing dominance. According to our data, the most effective for the analysis of holistic processing is a more detailed type of marking the AOIs, in which not only the main features (eyes, nose, mouth) are distinguished, but also the area of the nose bridge and nose.

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Identifying translation problems in English-Chinese sight translation

Translation and Interpreting Studies ◽

10.1075/tis.00033.su ◽

2019 ◽

Vol 14 (1) ◽

pp. 110-134 ◽

Cited By ~ 7

Author(s):

Wenchao Su ◽

Defeng Li

Keyword(s):

Eye Tracking ◽

Research Methods ◽

Noun Phrase ◽

Specific Problem ◽

Tracking Data ◽

Translation Process ◽

European Languages ◽

L1 And L2 ◽

Language Pair

Abstract Translation problems have received considerable attention among translation process researchers and different research methods have been used to identify them. Findings are sometimes inconsistent, and as these studies have mainly studied translation between European languages, little research has been conducted to explore the issue concerning non-European languages. To fill this gap, the present study investigates problem triggers in English-Chinese sight translation in both directions (L1 and L2 translation). using eye-tracking data (Dragsted 2012). Results suggest that the type and number of translation problems encountered by the translators are different in L1 and L2 sight translation and that language-pair specificity is at play during the process, indicated by two identified Chinese-specific problem triggers, namely, back-sloping comma and head-final noun phrase.

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Collaborative Use of a Shared System Interface: The Role of User Gaze—Gaze Convergence Index Based on Synchronous Dual-Eyetracking

Applied Sciences ◽

10.3390/app10134508 ◽

2020 ◽

Vol 10 (13) ◽

pp. 4508 ◽

Cited By ~ 1

Author(s):

Armel Quentin Tchanou ◽

Pierre-Majorique Léger ◽

Jared Boasen ◽

Sylvain Senecal ◽

Jad Adam Taher ◽

...

Keyword(s):

Eye Movements ◽

Eye Tracking ◽

Task Performance ◽

Tracking Data ◽

Nomological Network ◽

Practical Applications ◽

The Gaze ◽

Research Perspectives ◽

System Interfaces

Gaze convergence of multiuser eye movements during simultaneous collaborative use of a shared system interface has been proposed as an important albeit sparsely explored construct in human-computer interaction literature. Here, we propose a novel index for measuring the gaze convergence of user dyads and address its validity through two consecutive eye-tracking studies. Eye-tracking data of user dyads were synchronously recorded while they simultaneously performed tasks on shared system interfaces. Results indicate the validity of the proposed gaze convergence index for measuring the gaze convergence of dyads. Moreover, as expected, our gaze convergence index was positively associated with dyad task performance and negatively associated with dyad cognitive load. These results suggest the utility of (theoretical or practical) applications such as synchronized gaze convergence displays in diverse settings. Further research perspectives, particularly into the construct’s nomological network, are warranted.

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Random Spray Retinex Extensions Considering Region of Interest and Eye Movements

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2019.63.6.060403 ◽

2019 ◽

Vol 63 (6) ◽

pp. 60403-1-60403-6

Author(s):

Midori Tanaka ◽

Matteo Paolo Lanaro ◽

Takahiko Horiuchi ◽

Alessandro Rizzi

Keyword(s):

Information Processing ◽

Eye Movements ◽

Visual Field ◽

Eye Tracking ◽

Mathematical Description ◽

Visual Information ◽

Tracking System ◽

Region Of Interest ◽

Tracking Data ◽

Proposed Model

Abstract The Random spray Retinex (RSR) algorithm was developed by taking into consideration the mathematical description of Milano-Retinex. The RSR substituted random paths with random sprays. Mimicking some characteristics of the human visual system (HVS), this article proposes two variants of RSR adding a mechanism of region of interest (ROI). In the first proposed model, a cone distribution based on anatomical data is considered as ROI. In the second model, the visual resolution depending on the visual field based on the knowledge of visual information processing is considered as ROI. We have measured actual eye movements using an eye-tracking system. By using the eye-tracking data, we have simulated the HVS using test images. Results show an interesting qualitative computation of the appearance of the processed area around real gaze points.

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PyTrack: An end-to-end analysis toolkit for eye tracking

Behavior Research Methods ◽

10.3758/s13428-020-01392-6 ◽

2020 ◽

Vol 52 (6) ◽

pp. 2588-2603

Author(s):

Upamanyu Ghose ◽

Arvind A. Srinivasan ◽

W. Paul Boyce ◽

Hong Xu ◽

Eng Siong Chng

Keyword(s):

Statistical Analysis ◽

Eye Movements ◽

Eye Tracking ◽

Automated Analysis ◽

Movement Behavior ◽

High Temporal Resolution ◽

Technological Advancement ◽

Tracking Data ◽

End To End ◽

Parameters Of Interest

AbstractEye tracking is a widely used tool for behavioral research in the field of psychology. With technological advancement, we now have specialized eye-tracking devices that offer high sampling rates, up to 2000 Hz, and allow for measuring eye movements with high accuracy. They also offer high spatial resolution, which enables the recording of very small movements, like drifts and microsaccades. Features and parameters of interest that characterize eye movements need to be algorithmically extracted from raw data as most eye trackers identify only basic parameters, such as blinks, fixations, and saccades. Eye-tracking experiments may investigate eye movement behavior in different groups of participants and in varying stimuli conditions. Hence, the analysis stage of such experiments typically involves two phases, (i) extraction of parameters of interest and (ii) statistical analysis between different participants or stimuli conditions using these parameters. Furthermore, the datasets collected in these experiments are usually very large in size, owing to the high temporal resolution of the eye trackers, and hence would benefit from an automated analysis toolkit. In this work, we present PyTrack, an end-to-end open-source solution for the analysis and visualization of eye-tracking data. It can be used to extract parameters of interest, generate and visualize a variety of gaze plots from raw eye-tracking data, and conduct statistical analysis between stimuli conditions and subject groups.

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