Using eye movements to investigate word frequency effects in children’s sentence reading

While eye movements have been used widely to investigate how skilled adult readers process written language, relatively little research has used this methodology with children. This is unfortunate as, as we discuss here, eye-movement studies have significant potential to inform our understanding of children’s reading development. We consider some of the empirical and theoretical issues that arise when using this methodology with children, illustrating our points with data from an experiment examining word frequency effects in 8-year-old children’s sentence reading. Children showed significantly longer gaze durations to low than high-frequency words, demonstrating that linguistic characteristics of text drive children’s eye movements as they read. We discuss these findings within the broader context of how eye-movement studies can inform our understanding of children’s reading, and can assist with the development of appropriately targeted interventions to support children as they learn to read.

Word length and landing position effects during reading in children and adults

The present study examined the effects of word length on children’s eye movement behaviour when other variables were carefully controlled. Importantly, the results showed that word length influenced children’s reading times and fixation positions on words. Furthermore, children exhibited stronger word length effects than adults in gaze durations and refixations. Adults and children generally did not differ in initial landing positions, but did differ in refixation behaviour. Overall, the results indicated that while adults and children show similar effects of word length for early measures of eye movement behaviour, differences emerge in later measures.

A robust sclera segmentation algorithm

Sclera segmentation is shown to be of significant importance for eye and iris biometrics. However, sclera segmentation has not been extensively researched as a separate topic, but mainly summarized as a component of a broader task. This paper proposes a novel sclera segmentation algorithm for colour images which operates at pixel-level. Exploring various colour spaces, the proposed approach is robust to image noise and different gaze directions. The algorithm’s robustness is enhanced by a two-stage classifier. At the first stage, a set of simple classifiers is employed, while at the second stage, a neural network classifier operates on the probabilities’ space generated by the classifiers at stage 1. The proposed method was ranked the 1st in Sclera Segmentation Benchmarking Competition 2015, part of BTAS 2015, with a precision of 95.05% corresponding to a recall of 94.56%.

Antecedents of travellers' electronic word-of-mouth communication

Electronic word-of-mouth (eWOM) is recognised as a means of interpersonal communication and a powerful marketing tool. However, previous studies have focussed on related motivations, and limited attention has been given to understanding the antecedents of eWOM communication behaviour in the travel industry. This study proposes a full and partial mediation model, which brings together for the first time three key antecedents: adoption of electronic communication technology, consumer dis/satisfaction with travel consumption experience, and subjective norm. The model aims to understand the impact of these antecedents on travellers' attitude towards eWOM communication and intention to use eWOM communication media. The data were collected from international travellers (n = 524), and structural equation modelling is used to test the conceptual framework. The findings of the study suggest that overall attitude towards eWOM communication partially mediates the impact of the traveller's adoption of electronic communication technology and subjective norm, and fully mediates the impact of consumer dis/satisfaction with travel consumption experience on travellers' intention to use eWOM communication media.

On fusion for robust motion segmentation

While a multitude of motion segmentation algorithms have been presented in the literature, there has not been an objective assessment of different approaches to fusing their outputs. This paper investigates the application of 4 different fusion schemes to the outputs of 3 probabilistic pixel-level segmentation algorithms. We performed an extensive experimentation using 6 challenge categories from the changedetection.net dataset demonstrating that in general simple majority vote proves to be more effective than more complex fusion schemes.

Segmentation-level fusion for iris recognition

This paper investigates the potential of fusion at normalisation/segmentation level prior to feature extraction. While there are several biometric fusion methods at data/feature level, score level and rank/decision level combining raw biometric signals, scores, or ranks/decisions, this type of fusion is still in its infancy. However, the increasing demand to allow for more relaxed and less invasive recording conditions, especially for on-the-move iris recognition, suggests to further investigate fusion at this very low level. This paper focuses on the approach of multi-segmentation fusion for iris biometric systems investigating the benefit of combining the segmentation result of multiple normalisation algorithms, using four methods from two different public iris toolkits (USIT, OSIRIS) on the public CASIA and IITD iris datasets. Evaluations based on recognition accuracy and ground truth segmentation data indicate high sensitivity with regards to the type of errors made by segmentation algorithms.

Word juncture characteristics in world Englishes: a research report

The subtle juncture cues in older varieties of English such as Received Pronunciation can be difficult for speakers of new English varieties to perceive. This study looks at the perception of word juncture characteristics in three varieties of English (British, Hong Kong and Singapore) among British, Hong Kong and Singaporean listeners in order to widen our understanding of English juncture characteristics in general. We find that, even though reaction time data indicates that listeners perform quickest in the variety they are most familiar with, not only are juncture differences in British English difficult for Hong Kong and Singaporean listeners to perceive, they are also the most difficult for British listeners. Juncture characteristics in Hong Kong English are the easiest to distinguish among the three varieties.

Creating a non-word list to match 226 of the Snodgrass standardised picture set

Creating non-word lists is a necessary but time consuming exercise often needed when conducting behavioural language tasks involving lexical decision-making or non-word reading. The following article describes the process whereby we created a list of 226 non-words matching 226 of the Snodgrass picture set (Snodgrass & Vanderwart, 1980).The non-words were matched for number of syllables, stress pattern, number of phonemes, bigram count and presence and location of the target sound when relevant.