Handwritten and Audio Information Fusion for Mathematical Symbol Recognition

Abstract : Considerable efforts are being done within the scientific community to make as easier as possible the way that the human being converses with its machine. Handwriting and speech are two common ways used to achieve this goal and are probably among those which attracted much interest. In mathematical content recognition tasks, these two modalities are used with a certain success. This paper presents an architecture based on a speechhandwriting data fusion for isolated mathematical symbol recognition. Different fusion methods are explored. The results are very encouraging since recognition rates are increased comparatively to mono modality approaches.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-00615206
Contributor : Harold Mouchère <>
Submitted on : Thursday, August 18, 2011 - 11:26:02 AM
Last modification on : Wednesday, December 19, 2018 - 3:02:03 PM

Identifiers

  • HAL Id : hal-00615206, version 1

Citation

Sofiane Medjkoune, Harold Mouchère, Simon Petitrenaud, Christian Viard-Gaudin. Handwritten and Audio Information Fusion for Mathematical Symbol Recognition. 11th International Conference on Document Analysis and Recognition, ICDAR 2011, Sep 2011, Beijing, China. ⟨hal-00615206⟩

Share

Metrics

Record views

237