A method for transcribing an odor or an aroma into a colorimetric description comprising the following steps: - a first step of physico-chemical analysis of said odor or of said aroma in order to associate with it a physico-chemical description comprising a physico-chemical vector, comprising proportions (qm i) associated with a predetermined set of respective volatile molecules (Mi), - a second step of physico-chemical analysis of a set of so-called test odors and/or aromas (Ot) in order to assign to each test odor or aroma (Ot) of said set a so-called test physico-chemical description (PC t) comprising a so-called test physico-chemical vector (PQ t) comprising test proportions (qmt i) associated with said predetermined set of respective volatile molecules (Mi), - a step of assigning to the test odors and/or aromas (Ot) respective test colorimetric descriptions (DCt) comprising so-called test proportions (qct j) associated with a set of respective colors (Cj), - a step of assigning to the odor or to the aroma a colorimetric description comprising proportions (qc j) associated with said respective colors (Cj), said assignment step comprising a first step of assigning to the odor or to the aroma a theoretical colorimetric description comprising theoretical colorimetric proportions (qcT j) associated with said respective colors (Cj), this first assignment step being performed by means of a first artificial neural network exhibiting a layered architecture, by presenting to it, as input, the physico-chemical vector, said first neural network generating, as output, said theoretical colorimetric description, said first neural network being previously subjected to a first learning step during which there are supplied to it, as input, physico-chemical vectors (PQt) associated with the set of test odors and/or aromas, said first learning step being performed in a supervised manner by taking into account the test colorimetric descriptions associated with the respective set of test odors and/or aromas. - a first step of physico-chemical analysis of said odor or of said aroma in order to associate with it a physico-chemical description comprising a physico-chemical vector, comprising proportions (qm i) associated with a predetermined set of respective volatile molecules (Mi), - a second step of physico-chemical analysis of a set of so-called test odors and/or aromas (Ot) in order to assign to each test odor or aroma (Ot) of said set a so-called test physico-chemical description (PC t) comprising a so-called test physico-chemical vector (PQ t) comprising test proportions (qmt i) associated with said predetermined set of respective volatile molecules (Mi), - a step of assigning to the test odors and/or aromas (Ot) respective test colorimetric descriptions (DCt) comprising so-called test proportions (qct j) associated with a set of respective colors (Cj), - a step of assigning to the odor or to the aroma a colorimetric description comprising proportions (qc j) associated with said respective colors (Cj), said assignment step comprising a first step of assigning to the odor or to the aroma a theoretical colorimetric description comprising theoretical colorimetric proportions (qcT j) associated with said respective colors (Cj), this first assignment step being performed by means of a first artificial neural network exhibiting a layered architecture, by presenting to it, as input, the physico-chemical vector, said first neural network generating, as output, said theoretical colorimetric description, said first neural network being previously subjected to a first learning step during which there are supplied to it, as input, physico-chemical vectors (PQt) associated with the set of test odors and/or aromas, said first learning step being performed in a supervised manner by taking into account the test colorimetric descriptions associated with the respective set of test odors and/or aromas.