  The University of Sheffield (USFD) participated in the International Workshop
for Spoken Language Translation (IWSLT) in 2014. In this paper, we will
introduce the USFD SLT system for IWSLT. Automatic speech recognition (ASR) is
achieved by two multi-pass deep neural network systems with adaptation and
rescoring techniques. Machine translation (MT) is achieved by a phrase-based
system. The USFD primary system incorporates state-of-the-art ASR and MT
techniques and gives a BLEU score of 23.45 and 14.75 on the English-to-French
and English-to-German speech-to-text translation task with the IWSLT 2014 data.
The USFD contrastive systems explore the integration of ASR and MT by using a
quality estimation system to rescore the ASR outputs, optimising towards better
translation. This gives a further 0.54 and 0.26 BLEU improvement respectively
on the IWSLT 2012 and 2014 evaluation data.
