The main goal of this work is to set up a multimodal system dedicated to mathematical expression recognition. In the proposed architecture, the transcription coming out from a speech recognition system is used to disambiguate the result of a handwriting recognition module. A set of keywords is built from the transcription module and used to rescore the outputs of both the handwriting classifier and the structural analysis module. Performances evaluated on theHAMEX dataset show a significant improvement over a single modality system.