gaze tracking

Cognition-aware Cognate Detection

Automatic detection of cognates helps downstream NLP tasks of Machine Translation, Cross-lingual Information Retrieval, Computational Phylogenetics and Cross-lingual Named Entity Recognition. Previous approaches for the task of cognate detection use …

A Survey on Using Gaze Behaviour for Natural Language Processing

Gaze behaviour has been used as a way to gather cognitive information for a number of years. In this paper, we discuss the use of gaze behaviour in solving different tasks in natural language processing (NLP) without having to record it at test time. …

Cognitively Aided Zero-Shot Automatic Essay Grading

Automatic essay grading (AEG) is a process in which machines assign a grade to an essay written in response to a topic, called the prompt. Zero-shot AEG is when we train a system to grade essays written to a new prompt which was not present in our …

Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour

The gaze behaviour of a reader is helpful in solving several NLP tasks such as automatic essay grading. However, collecting gaze behaviour from readers is costly in terms of time and money. In this paper, we propose a way to improve automatic essay …

Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour

Predicting a reader's rating of text quality is a challenging task that involves estimating different subjective aspects of the text, like structure, clarity, etc. Such subjective aspects are better handled using cognitive information. One such …

New Vistas to study Bhartṛhari: Cognitive NLP

A sentence is an important notion in the Indian grammatical tradition. The collection of the definitions of a sentence can be found in the text ‘Vākyapadīya’ written by Bhartṛhari in fifth century C.E. The grammarian-philosopher Bhartṛhari and his …

Scanpath Complexity: Modeling Reading Effort using Gaze Information

Measuring reading effort is useful for practical purposes such as designing learning material and personalizing text comprehension environment. We propose a quantification of reading effort by measuring the complexity of eye-movement patterns of …

Harnessing Cognitive Features for Sarcasm Detection

In this paper, we propose a novel mechanism for enriching the feature vector, for the task of sarcasm detection, with cognitive features extracted from eye-movement patterns of human readers. Sarcasm detection has been a challenging research problem, …

Leveraging Cognitive Features for Sentiment Analysis

Sentiments expressed in user-generated short text and sentences are nuanced by subtleties at lexical, syntactic, semantic and pragmatic levels. To address this, we propose to augment traditional features used for sentiment analysis and sarcasm …

Predicting Readers' Sarcasm Understandability by Modeling Gaze Behavior

Sarcasm understandability or the ability to understand textual sarcasm depends upon readers’ language proficiency, social knowledge, mental state and attentiveness. We introduce a novel method to predict the sarcasm understandability of a reader. …