We present S2TT, an integrated speech-to-text translation system based on POCKETSPHINX and MOSES. It is compared to different baselines based on ANTS --- the broadcast news transcription system developed at LORIA's Speech group, MOSES and Google's translation tools. A small corpus of reference transcriptions of broadcast news from the evaluation campaign ESTER2 was translated by human experts for evaluation. The Word Error Rate (WER) of the recognition stage of both systems are evaluated, and BLEU is used to score the translations. Furthermore, the reference transcriptions are automatically translated using MOSES and GOOGLE in order to evaluate the impact of recognition errors on translation quality.