Résumé : This paper presents CLIPS laboratory activities in speech recognition related to language model adaptation and acoustic model adaptation in the NESPOLE! European project. ASR system needed to be adapted in two ways. The language model had to deal with task specific vocabulary and the acoustic model had to be robust to VoIP (Voice over IP) speech. It was shown that Internet, as a very large source of text, can be a very interesting database for spoken language modelling adaptation. The influence of different VoIP codecs on the performance of our speech recognition engine was investigated and a new strategy was proposed to cope with degradation due to low bitrate coding. The acoustic models of the speech recognition system were trained with transcoded speech. Results have shown that this strategy allows to recover acceptable performance for the NESPOLE! project context.