Text Alignment from Bimodal Mathematical Expression Sources.

In this paper we propose a new approach to merge mathematical expression recognition results coming from handwriting and speech modalities. Using a bimodal description of mathematical expressions allows taking advantage of the complementarities between both signals, and can disambiguate situations were a single modality would not be clear enough. To combine the signals coming from both modalities, we propose to represent them in the same space as a textual description. First, from the handwriting signal, we generate the Nbest mathematical expressions, each of them is next translated as different possible strings. From the audio signal, an automatic speech recognition system provides a transcript, which is also available as a string. A string comparison algorithm is achieved to select the best mathematical expressions. This bimodal system is evaluated on real bimodal data from the HAMEX dataset and the results are compared to a single modality (handwriting) based system.