Team ReadMe at CMCL 2021 Shared Task: Predicting Human Reading Patterns by Traditional Oculomotor Control Models and Machine Learning

2021-01-01
Balkoca, Alisan
Algan, A. Can
Acartürk, Cengiz
Çöltekin, Çǎgri
©2021 Association for Computational Linguistics.This system description paper describes our participation in CMCL 2021 shared task on predicting human reading patterns. Our focus in this study is making use of well-known, traditional oculomotor control models and machine learning systems. We present experiments with a traditional oculomotor control model (the EZ Reader) and two machine learning models (a linear regression model and a recurrent network model), as well as combining the two different models. In all experiments we test effects of features well-known in the literature for predicting reading patterns, such as frequency, word length and word predictability. Our experiments support the earlier findings that such features are useful when combined. Furthermore, we show that although machine learning models perform better in comparison to traditional models, combination of both gives a consistent improvement for predicting multiple eye tracking variables during reading.
11th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2021

Suggestions

Representing temporal knowledge in connectionist expert systems
Alpaslan, Ferda Nur (1996-09-27)
This paper introduces a new temporal neural networks model which can be used in connectionist expert systems. Also, a Variation of backpropagation algorithm, called the temporal feedforward backpropagation algorithm is introduced as a method for training the neural network. The algorithm was tested using training examples extracted from a medical expert system. A series of experiments were carried out using the temporal model and the temporal backpropagation algorithm. The experiments indicated that the alg...
Interacting fuzzy multimodel intelligent tracking system for swift target manoeuvres
Gokkus, L; Erkmen, Aydan Müşerref; Tekinalp, Ozan (1997-09-11)
This paper focuses on the generation of an intelligent tracker module equipped with a wavelet based neural network that learns predictions from past experience. The perception of actual tar et manoeuvre and prediction of its future states are achieved in this work by "projecting" actual observations into decision spaces of local fuzzy predictions based on independent prototypical trajectory types: linear, parabolic and square root type trajectory. Decentralized tracking decisions are thus generated which ar...
Functional Size of a Real-Time System
Desharnais, Jean-Marc; Abran, Alain; Dikici, Pinar Efe; Ilis, Mert Can; Karaca, Irfan Nuri;( Abstracts: This paper presents a case study on the implementation of IFPUG FPA and COSMIC software measurement methods for a small real-time system. The two methods were applied separately to measure the functional size of the same software. The main objective of this paper is to explore, through a case study, the issue of the measurement adequacy of each measurement method to capture the functional size of real-time software. For the practitioners, the real issue is that such a 'number' represent adequately the functional size. This number should take into consideration the particularities of specific real-time software and be sensitive to small variations of functionality.; 2009-11-06)
This paper presents a case study on the implementation of IFPUG FPA and COSMIC software measurement methods for a small real-time system. The two methods were applied separately to measure the functional size of the same software. The main objective of this paper is to explore, through a case study, the issue of the measurement adequacy of each measurement method to capture the functional size of real-time software. For the practitioners, the real issue is that such a 'number' represent adequately the funct...
Position estimation for timing belt drives of precision machinery using structured neural networks
KILIÇ, Ergin; DOĞRUER, CAN ULAŞ; Dölen, Melik; Koku, Ahmet Buğra (2012-05-01)
This paper focuses on a viable position estimation scheme for timing-belt drives using artificial neural networks. In this study, the position of a carriage (load) is calculated via a structured neural network topology accepting input from a position sensor on the actuator side of the timing belt. The paper presents a detailed discussion on the source of transmission errors. The characteristics of the error in different operation regimes are exploited to construct different network topologies. That is, a re...
Hybrid Approach for Mobile Couriers Election in Smart-cities
Al-Turjman, Fadi (2016-11-10)
In this paper we propose a hybrid heuristic approach for public data delivery under ultra-large-scale smart-city settings. In this approach, public transportation vehicles are going into election process to be utilized as Mobile Couriers (MCs) that read public Access Points (APs) data loads and relay it back to a central processing base-station. We also introduce a cost-based fitness function for the MCs election in the smart-city project which forms a real implementation for the Internet of Things (IoT) pa...
Citation Formats
A. Balkoca, A. C. Algan, C. Acartürk, and Ç. Çöltekin, “Team ReadMe at CMCL 2021 Shared Task: Predicting Human Reading Patterns by Traditional Oculomotor Control Models and Machine Learning,” presented at the 11th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2021, Virtual, Online, 2021, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85123199562&origin=inward.