Work

GazeReader: Detecting Unknown Word Using Webcam for English as a Second Language (ESL) Learners

Year: 2023

Type: conference-paper

Abstract: Automatic unknown word detection techniques can enable new applications for assisting English as a Second Language (ESL) learners, thus improving their reading experiences. However, most modern unknown word detection methods require dedicated eye-tracking devices with high precision that are not easily accessible to end-users. In this work, we propose GazeReader, an unknown word detection method only using a webcam. GazeReader tracks the learner’s gaze and then applies a transformer-based machine learning model that encodes the text information to locate the unknown word. We applied knowledge enhancement including term frequency, part of speech, and named entity recognition to improve the performance. The user study indicates that the accuracy and F1-score of our method were 98.09% and 75.73%, respectively. Lastly, we explored the design scope for ESL reading and discussed the findings.

Source: CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA)

DOI: 10.1145/3544549.3585790

Authors: Jiexin Ding, Bowen Zhao, Yuqi Huang, Yuntao Wang, Yuanchun Shi

Institutions: Tsinghua University, University of Washington

Language: English

Topic: Gaze Tracking and Assistive Technology

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: bronze

Funders: National Natural Science Foundation of China, Tsinghua University