The main topic of this thesis is a novel method for the automatic acquisition of mathematical formulas using natural handwriting, speech, and pen gestures. The proposed approach features the integration of all necessary system components in an expectation-driven, single-stage probabilistic decoding procedure which transforms online handwritten and spoken input to a semantic representation of mathematical formulas. An innovation in the field of online formula recognition lies in a statistical assessment of two-dimensional symbol distributions - including also font size variations - within the framework of a context-free grammar. Thus, the structural formula analysis is smoothly embedded into this integral system architecture. As a result, this approach greatly simplifies the problem of character segmentation. Another system feature is the automatic translation of handwritten and typeset formulas into spoken output.
«The main topic of this thesis is a novel method for the automatic acquisition of mathematical formulas using natural handwriting, speech, and pen gestures. The proposed approach features the integration of all necessary system components in an expectation-driven, single-stage probabilistic decoding procedure which transforms online handwritten and spoken input to a semantic representation of mathematical formulas. An innovation in the field of online formula recognition lies in a statistical ass...
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