The ANR project EmotiRob aims at conceiving and realizing a companion robot which interacts emotionally with fragile children. However, the project MAPH which is an extension of EmotiRob tries to extend the cognitive abilities of the robot to implement a linguistic interaction with the child. For this, we studied a children corpus and got semantic links that could exist between each pair of words. This corpus elaborated by D. Bassano has been used to evaluate language development among children under five. Using this corpus, we tried to make a taxonomy in accordance with the conceptual world of children and tested its validity. Using the taxonomy and the semantic properties that we attributed to the corpus words, we defined rapprochement coefficients between words in order to generate new sentences, answer the child questions and play with him. As a perspective for this, we envisage to make the robot able of enriching its vocabulary, and to define new learning patterns basing on its reactions.
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