Arkady Arkhangorodsky


2020

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DiDi Labs’ End-to-end System for the IWSLT 2020 Offline Speech TranslationTask
Arkady Arkhangorodsky | Yiqi Huang | Amittai Axelrod
Proceedings of the 17th International Conference on Spoken Language Translation

This paper describes the system that was submitted by DiDi Labs to the offline speech translation task for IWSLT 2020. We trained an end-to-end system that translates audio from English TED talks to German text, without producing intermediate English text. We use the S-Transformer architecture and train using the MuSTC dataset. We also describe several additional experiments that were attempted, but did not yield improved results.