Journal Article

Discovering the Potential of Automated Phraseological Interference Error Detection: A Transformer-Based Approach

Kharlamova, Darya

2026

Overview

Formulaic language … may comprise strings of letters, words, sounds, or other elements, contiguous or non-contiguous, of any length, size, frequency, degree of compositionality, literality/figurativeness, abstractness and complexity, not necessarily assumed to be stored, retrieved or processed whole, but that necessarily enjoy a degree of conventionality or familiarity among … speakers of a language community … and that hold a strong relationship in communicating meaning. Errors of this type are typically addressed by EFL teachers, but due to globalization and ever-increasing intercultural and international cooperation, the number of EFL students is growing exponentially, with many relying on self-learning. [...]they would benefit greatly from a tool that could highlight errors resulting from L1 interference. Transformer fine-tuning principles and capabilities in error detection Before examining the data collected and the experiments conducted, we explain the basics of the mechanisms underlying neural networks, training, fine-tuning and the conditions required for this process to work, in addition to referring to the existing research on grammatical error detection and the correction process. [...]the numerical representation made by the last layer is converted into human-readable data which is compared to the expected result (e.g., a correct class, a correct answer to the question, etc.).

• Publisher: White Rose University Press
• Subject: automated error detection / Cooperation / english / English as a second language / English as a second language instruction / Error analysis / Error correction & detection / Errors / Experiments / Familiarity / Formulaic language / Globalization / International cooperation / l2 acquisition / Language acquisition / language interference / Learning / Learning transfer / Mathematical functions / Native languages / Neural networks / Neurons / phraseology / russian / Second language learning / Self instruction / Teachers