The multiplication of handheld devices using the pen (electronic book, tablet PC, PDA, smart phone...) as a way of interaction, require an efficient recognition system in order to substitute both keyboard and mouse. In this paper, we present a new writer-independent system dedicated to the automatic recognition of on-line texts. This system uses a very large French lexicon (200,000 words) which cover a vast field of application. This recognition process is based on the activation-verification model proposed in perceptive psychology. A set of experts encodes the input signal and extract probabilistic informations at several levels of abstraction (geometrical and morphological). A neural expert generates a tree of segmentation hypotheses. This tree is explored by a probabilistic fusion expert that uses all the available informations (geometrical and lexical) in order to provide the best transcription of the input signal.
['Lo ¨ õc Oudot', 'Lionel Prevost', 'Maurice Milgram']
An activation-verification model for on-line texts recognition