The computer learner corpus: a versatile new source of data for SLA research
By Sylviane Granger. 1998
Subfields: Evaluation & Benchmarks
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In Evaluation & Benchmarks
- Marcin Junczys-Dowmunt
- Shin'ichiro Ishikawa
- Mariano Felice
- Roman Grundkiewicz
- Kenneth Heafield
- Christopher Bryant
- B. Altenberg
- Øistein E. Andersen
Citations in the corpus
- Improving Grammatical Error Correction with Machine Translation Pairs (2019, unknown): “, 2011) and W&I+LOCNESS datasets (Bryant et al., 2019; Granger, 1998).”
- The BEA-2019 Shared Task on Grammatical Error Correction (2019, methodology): “To do this, we used the LOCNESS corpus, a collection of approximately 400 essays written by native British and American undergraduates on various topics (Granger, 1998).”
- Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction (2020, unknown): “Following recent work in English GEC, we conduct experiments in the same setting with the restricted track of the BEA-2019 GEC shared task (Bryant et al., 2019), using FCE (Yannakoudakis et al., 2011), Lang-8 Corpus of Learner English (Mizu-moto et al., 2011), NUCLE (Dahlmeier et al., 2013) and W&I+”
- The grammatical and lexical patterning of MAKE in native and non-native student writing (2001, methodology): “Hence, one important conclusion to be drawn from this part of the study is that there is a need for a wider range of learner data and detailed corpus-based contrastive studies to supplement the learner data examined here (see Granger 1998).”
- The ICNALE and Sophisticated Contrastive Interlanguage Analysis of Asian Learners of English (2013, methodology): “Granger (1998) introduces two types of CIA: One is the NL vs. IL contrast, namely, a comparison of native language and interlanguage to “uncover the features of non-nativeness of learner language.””
- Erroneous data generation for Grammatical Error Correction (2019, background): “5 with ERRANT (Bryant et al., 2017) on the ABCN test, GLEU (Sakaguchi et al., 2016) on the JFLEG test set (Napoles et al., 2017).”
- Neural Grammatical Error Correction Systems with Unsupervised Pre-training on Synthetic Data (2019, methodology): “, 2013), W&I+LOCNESS data sets (Bryant et al., 2019; Granger, 1998), and a preprocessed version of the Lang-8 Corpus of Learner English (Mizumoto et al.”