Design issues of iDICT: a gaze-assisted translation aid
ETRA '00 Proceedings of the 2000 symposium on Eye tracking research & applications
Fitting of mixtures with unspecified number of components using cross validation distance estimate
Computational Statistics & Data Analysis
Predictive Models for Sequence Modelling, Application to Speech and Character Recognition
Adaptive Processing of Sequences and Data Structures, International Summer School on Neural Networks, "E.R. Caianiello"-Tutorial Lectures
Combining eye movements and collaborative filtering for proactive information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Expectation maximization algorithms for conditional likelihoods
ICML '05 Proceedings of the 22nd international conference on Machine learning
What do you want to do next: a novel approach for intent prediction in gaze-based interaction
Proceedings of the Symposium on Eye Tracking Research and Applications
A robust realtime reading-skimming classifier
Proceedings of the Symposium on Eye Tracking Research and Applications
On-condition maintenance of diesel engines modelled by a hidden Markov model
AIC'10/BEBI'10 Proceedings of the 10th WSEAS international conference on applied informatics and communications, and 3rd WSEAS international conference on Biomedical electronics and biomedical informatics
Exploring gaze data for determining user learning with an interactive simulation
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
Modeling video viewing behaviors for viewer state estimation
Proceedings of the 20th ACM international conference on Multimedia
How impulsivity affects consumer decision-making in e-commerce
Electronic Commerce Research and Applications
Proceedings of the 2013 international conference on Intelligent user interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Predicting where we look from spatiotemporal gaps
Proceedings of the 15th ACM on International conference on multimodal interaction
Learning aspects of interest from Gaze
Proceedings of the 6th workshop on Eye gaze in intelligent human machine interaction: gaze in multimodal interaction
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We study how processing states alternate during information search tasks. Inference is carried out with a discriminative hidden Markov model (dHMM) learned from eye movement data, measured in an experiment consisting of three task types: (i) simple word search, (ii) finding a sentence that answers a question and (iii) choosing a subjectively most interesting title from a list of ten titles. The results show that eye movements contain necessary information for determining the task type. After training, the dHMM predicted the task for test data with 60.2% accuracy (pure chance 33.3%). Word search and subjective interest conditions were easier to predict than the question-answer condition. The dHMM that best fitted our data segmented each task type into three hidden states. The three processing states were identified by comparing the parameters of the dHMM states to literature on eye movement research. A scanning type of eye behavior was observed in the beginning of the tasks. Next, participants tended to shift to states reflecting reading type of eye movements, and finally they ended the tasks in states which we termed as the decision states.