Building and Using Corpora of Non-Native Czech

Investigating language acquisition by non-native learners helps to understand important linguistic issues and develop teaching methods, better suited both to the specific target language and to the learner. These tasks can now be based on empirical evidence from learner corpora. A learner corpus consists of language produced by language learners, typically learners of a second or foreign language (L2). Such corpora may be equipped with morphological and syntactic annotation, together with the detection, correction and categorization of non-standard linguistic phenomena. The tasks of designing, compiling, annotating and presenting such corpora are often very much unlike those routinely applied to standard corpora. There may be no standard or obvious solutions: the approach to the tasks is often seen as an answer to a specific research goal rather than as a service to a wider community of researchers and practitioners. Our aim is to investigate some of the challenges, based on a learner corpus of Czech in comparison to several other learner corpora. After an overview of learner corpora around the world in §2 and a brief presentation of several releases of a learner corpus of Czech in §3, we examine issues inherent to the process of compiling, annotating and using such corpora, including automatic identification of errors, the design and application of error taxonomy, and a user-friendly search tool, suited to a complex annotation (§4).