Daniel Déchelotte

Learn More
—This paper describes an approach for computing a consensus translation from the outputs of multiple machine translation (MT) systems. The consensus translation is computed by weighted majority voting on a confusion network, similarly to the well-established ROVER approach of Fiscus for combining speech recognition hypotheses. To create the confusion(More)
This paper describes our statistical machine translation systems based on the Moses toolkit for the WMT08 shared task. We address the Europarl and News conditions for the following language pairs: English with French, Ger-man and Spanish. For Europarl, n-best rescor-ing is performed using an enhanced n-gram or a neuronal language model; for the News(More)
This paper presents a two-way speech translation system that is completely hosted on an off-the-shelf handheld device. Specifically, this end-to-end system includes an HMM-based large vocabulary continuous speech recognizer (LVCSR) for both English and Chinese using statistical Ò-grams, a two-way translation system between English and Chinese, and, a(More)
The purpose of this work is to explore the integration of morphosyntactic information into the translation model itself, by enriching words with their morphosyntac-tic categories. We investigate word dis-ambiguation using morphosyntactic categories , n-best hypotheses reranking, and the combination of both methods with word or morphosyntactic n-gram(More)
  • 1