This paper describes the two systems developed by the LIUM laboratory for the 2010 IWSLT evaluation campaign. We participated to the new English to French TALK task. We developed two systems, one for each evaluation condition, both being statistical phrase-based systems using the the Moses toolkit. Several approaches were investigated. This paper describes the systems developed by the LIUM laboratory for the 2010 IWSLT evaluation campaign. This year, a new task (named TALK task) has been proposed, which is based on the TED talks and consists in translating the talks transcriptions from English to French. For this evaluation, two submissions were required, as two input conditions for translation were proposed. The first, called Correct Recognition Results (CRR) condition, uses the Automatic Speech Recognition (ASR) manual transcription as input, and the second, called ASR condition, uses an automatic speech recognition output. Thus we developed two specific systems, one for each input condition. The remainder of this paper is structured as follows: in section 2, we describe the individual systems setup and the specific strategies for translating in ASR condition. Particular approaches and issues like the use of ASR lattices or segmentation problems are discussed in section 3, then experimental results are summarized in section 4. The paper concludes with a discussion on future research issues in section 5.
['Anthony Rousseau', 'Loïc Barrault', 'Paul Deléglise', 'Yannick Estève']
LIUM's Statistical Machine Translation System for IWSLT 2010