‘Calling on the classical phone’: a distributional model of adjective-noun errors in learners’ English
Year: 2016
Type: conference-paper
Abstract: In this paper we discuss three key points related to error detection (ED) in learners’ English. We focus on content word ED as one of the most challenging tasks in this area, illustrating our claims on adjective–noun (AN) combinations. In particular, we (1) investigate the role of context in accurately capturing semantic anomalies and implement a system based on distributional topic coherence, which achieves state-of-the-art accuracy on a standard test set; (2) thoroughly investigate our system’s performance across individual adjective classes, concluding that a class-dependent approach is beneficial to the task; (3) discuss the data size bottleneck in this area, and highlight the challenges of automatic error generation for content words.
DOI: 10.17863/cam.9931
Authors: Herbelot, A, Kochmar, E
Institutions: University of Trento, University of Cambridge
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2573371028