DiDi Labs' End-to-end System for the IWSLT 2020 Offline Speech TranslationTask

Arkady Arkhangorodsky, Yiqi Huang, Amittai Axelrod

Abstract: 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.