Parallel corpus in analysing Czech spoken expressions and their equivalents in English, French, and Polish

Adrian Jan Zasina (Charles University, Prague)

FULL TEXT

ABSTRACT (en)

This paper uses corpus data to analyse spoken expressions and discourse markers in Czech, applying these findings to corpus-based exercises for learners of Czech as a foreign language. The analytical section highlights the usefulness of parallel corpus in identifying suitable translation equivalents for prevalent Czech spoken vocabulary in English, French, and Polish as native languages from the learner’s perspective. The methodology outlines the process of finding appropriate translation equivalents in film subtitles, considering both meaning and spoken register. The pedagogical section introduces three corpus-based exercises designed to improve conversational skills, featuring authentic texts that familiarise learners with spoken vocabulary. This research builds on previous studies of the English language that did not use parallel corpora to identify translation equivalents in learners’ native languages — an essential factor for understanding a foreign language. In addition, tailor-made corpus-based exercises can be seamlessly integrated into everyday classroom activities to enhance language awareness among non-native speakers.

KEYWORDS (en)

corpus, corpus-based exercises, Czech, data-driven learning, discourse markers, speaking skills, spoken expressions

DOI

https://doi.org/10.14712/18059635.2024.2.2

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