Learner Corpus

Learner corpora are collections of language data produced by second-language learners, serving as valuable resources for research in second language acquisition, language teaching, and automated language processing. Current research focuses on developing and annotating these corpora with diverse features, including grammatical error types and fluency scores, often employing machine learning models like binary classifiers and those based on neural network architectures for tasks such as error detection and fluency assessment. These corpora are crucial for advancing both theoretical understanding of language learning and the development of practical applications like computer-assisted language learning tools and automated grammatical error correction systems.