TU Darmstadt / ULB / TUbiblio

Predicting the Spelling Difficulty of Words for Language Learners

Beinborn, Lisa ; Zesch, Torsten ; Gurevych, Iryna (2016)
Predicting the Spelling Difficulty of Words for Language Learners.
San Diego, CA, USA
Conference or Workshop Item, Bibliographie

Abstract

In many language learning scenarios, it is important to anticipate spelling errors. We model the spelling difficulty of words with new features that capture phonetic phenomena and are based on psycholinguistic findings. To train our model, we extract more than 140,000 spelling errors from three learner corpora covering English, German and Italian essays. The evaluation shows that our model can predict spelling difficulty with an accuracy of over 80% and yields a stable quality across corpora and languages. In addition, we provide a thorough error analysis that takes the native language of the learners into account and provides insights into cross-lingual transfer effects.

Item Type: Conference or Workshop Item
Erschienen: 2016
Creators: Beinborn, Lisa ; Zesch, Torsten ; Gurevych, Iryna
Type of entry: Bibliographie
Title: Predicting the Spelling Difficulty of Words for Language Learners
Language: English
Date: 2016
Book Title: Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications held in conjunction with NAACL 2016
Event Location: San Diego, CA, USA
URL / URN: http://m-mitchell.com/NAACL-2016/BEA/pdf/BEA1108.pdf
Corresponding Links:
Abstract:

In many language learning scenarios, it is important to anticipate spelling errors. We model the spelling difficulty of words with new features that capture phonetic phenomena and are based on psycholinguistic findings. To train our model, we extract more than 140,000 spelling errors from three learner corpora covering English, German and Italian essays. The evaluation shows that our model can predict spelling difficulty with an accuracy of over 80% and yields a stable quality across corpora and languages. In addition, we provide a thorough error analysis that takes the native language of the learners into account and provides insights into cross-lingual transfer effects.

Uncontrolled Keywords: UKP_a_WALL;UKP_p_AutoExerGen;UKP_a_ENLP;UKP_reviewed
Identification Number: TUD-CS-2016-0077
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 1994 Adaptive Preparation of Information from Heterogeneous Sources
Date Deposited: 31 Dec 2016 14:29
Last Modified: 24 Jan 2020 12:03
PPN:
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details