We present a recurrent encoder-decoder deep neural network architecture that directly
translates speech in one language into text in another. The model does not explicitly …

We present an attention-based sequence-to-sequence neural network which can directly
translate speech from one language into speech in another language, without relying on an …

Over its three decade history, speech translation has experienced several shifts in its
primary research themes; moving from loosely coupled cascades of speech recognition and …

In this paper we present a tool for the evaluation of translation quality. First, the typical
requirements of such a tool in the framework of machine translation (MT) research are …

Current machine translation (MT) systems are still not perfect. In practice, the output from
these systems needs to be edited to correct errors. A way of increasing the productivity of the …

This article describes in detail an n-gram approach to statistical machine translation. This
approach consists of a log-linear combination of a translation model based on n-grams of …

Multimodal machine translation involves drawing information from more than one modality,
based on the assumption that the additional modalities will contain useful alternative views …

In speech translation, we are faced with the problem of how to couple the speech
recognition process and the translation process. Starting from the Bayes decision rule for …

In statistical natural language processing we always face the problem of sparse data. One
way to reduce this problem is to group words into equivalence classes which is a standard …

In this work, new approaches for machine translation using statistical methods are
described. In addition to the standard source-channel approach to statistical machine …