Lexical Signatures in Foreign Language Free-Form Texts
Abstract This paper presents an investigation into the extent to which the lexical choices made by learners of a second language (L2) are distinctive. It follows on from an earlier paper by the same authors in which a neural network was successfully trained to mark a set of texts produced by L2 learners to the same standard, within broad categories, as had been awarded by experienced human markers. For this present paper, we examined a set of L2 texts and searched them for unique lexical choices (‘lexical signatures’). The results suggest a possible explanation for the success of the neural-network trial, and may have some practical implications for determining the levels of achievement reached by L2 learners.
References (2)
References
HOLMES, D.I. (1994) : Authorship attribution. Computers and the Humanities, 28 (2), 87-106.
MEARA, P.M., RODGERS, C. and JACOBS, G. (2000) : Computational assessment of texts written by L2 speakers. System, 281, 345-354.
Cited by (1)
Cited by one other publication
Panagiotopoulos, Alexandra & Sabine Bergler
2014.
How Predictive Is Tense for Language Profiency? A Cautionary Tale. In
Human-Inspired Computing and Its Applications [
Lecture Notes in Computer Science, 8856],
► pp. 139 ff.
This list is based on CrossRef data as of 6 august 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers.
Any errors therein should be reported to them.