Speech recognition technology suffers from a lack of robustness which limits its usability for fully automated speech-to-text transcription, and manual correction is generally required to obtain perfect transcripts. In this paper, we propose a general scheme for semi-automatic transcription, in which the system and the transcriptionist contribute jointly to the speech transcription. In order to reduce the correction time, we evaluate various strategies aiming to guide the trans-criptionist towards the critical areas of transcripts. These strategies are based on graph density-based criterion and two semantic consistency criterion ; using a corpus-based method and a web-search engine. Results show semantic information must be integrated into the interactive decoding process.