2 |
Modeling Bilingual Lexical Processing Through Code-Switching Speech: A Network Science Approach
|
|
|
|
In: Front Psychol (2021)
|
|
BASE
|
|
Show details
|
|
3 |
Corrigendum: Modeling Bilingual Lexical Processing Through Code-Switching Speech: A Network Science Approach
|
|
|
|
In: Front Psychol (2021)
|
|
BASE
|
|
Show details
|
|
4 |
A Network Science Approach to Bilingual Code-switching
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2021)
|
|
BASE
|
|
Show details
|
|
5 |
TASK-EVOKED PUPILLARY RESPONSES (TEPR) IN SPANISH-ENGLISH BILINGUALS' PROCESSING OF RELATIVE CLAUSES ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
ETS Corpus of Non-Native Written English
|
|
|
|
Abstract:
*Introduction* ETS Corpus of Non-Native Written English was developed by Educational Testing Service and is comprised of 12,100 English essays written by speakers of 11 non-English native languages as part of an international test of academic English proficiency, TOEFL (Test of English as a Foreign Language). The test includes reading, writing, listening, and speaking sections and is delivered by computer in a secure test center. This release contains 1,100 essays for each of the 11 native languages sampled from eight topics with information about the score level (low/medium/high) for each essay. The corpus was developed with the specific task of native language identification in mind, but is likely to support tasks and studies in the educational domain, including grammatical error detection and correction and automatic essay scoring, in addition to a broad range of research studies in the fields of natural language processing and corpus linguistics. For the task of native language identification, the following division is recommended: 82% as training data, 9% as development data and 9% as test data, split according to the file IDs accompanying the data set. *Data* The data is sampled from essays written in 2006 and 2007 by test takers whose native languages were Arabic, Chinese, French, German, Hindi, Italian, Japanese, Korean, Spanish, Telugu, and Turkish. The essays are presented in both original raw and tokenized forms and presented in UTF-8 formatted text files. Also included are the prompts (topics) for the essays and metadata about the test takers' proficiency level. *Samples* Please view this original and tokenized samples. *Updates* In July 2014, 1,100 files were added to the corpus, bringing the total number of tokenized and original files to 12,100. All copies distributed after that date contain the full data set.
|
|
URL: https://catalog.ldc.upenn.edu/LDC2014T06
|
|
BASE
|
|
Hide details
|
|
8 |
ETS Corpus of Non-Native Written English ; Educational Testing Service Corpus of Non-Native Written English
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Using parse features for preposition selection and error detection
|
|
|
|
In: Tetreault, Joel, Foster, Jennifer orcid:0000-0002-7789-4853 and Chodorow, Martin (2010) Using parse features for preposition selection and error detection. In: ACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, 11-16 July 2010, Uppsala, Sweden. (2010)
|
|
BASE
|
|
Show details
|
|
|
|