Charles Explorer logo
🇬🇧

CUNI Neural ASR with Phoneme-Level Intermediate Step for Non-Native SLT at IWSLT 2020

Publication at Faculty of Mathematics and Physics |
2020

Abstract

In this paper, we present our submission to the Non-Native Speech Translation Task for IWSLT 2020. Our main contribution is a proposed speech recognition pipeline that consists of an acoustic model and a phoneme-to grapheme model.

As an intermediate representation, we utilize phonemes. We demonstrate that the proposed pipeline surpasses commercially used automatic speech recognition (ASR) and submit it into the ASR track.

We complement this ASR with off-the-shelf MT systems to take part also in the speech translation track.