ArzEn-ST: A Three-way Speech Translation Corpus for Code-Switched Egyptian Arabic - English

Abstract

We present our work on collecting ArzEnST, a code-switched Egyptian Arabic - English Speech Translation Corpus. This corpus is an extension of the ArzEn speech corpus, which was collected through informal interviews with bilingual speakers. In this work, we collect translations in both directions, monolingual Egyptian Arabic and monolingual English, forming a three-way speech translation corpus. We make the translation guidelines and corpus publicly available. We also report results for baseline systems for machine translation and speech translation tasks. We believe this is a valuable resource that can motivate and facilitate further research studying the codeswitching phenomenon from a linguistic perspective and can be used to train and evaluate NLP systems.