Detection of Textual Motifs and Multichannel Deep Learning with LASLA lemmatized and tagged files: two case studies

We wish to explore the difference between Deep Learning applied simply to the lexical forms of a text and Multichannel Deep Learning, which also takes into account the lemmas and morphosyntax. More precisely, the idea is to better understand the criteria, that is the ‘textual motifs’ on which Deep Learning relies to offer its classification. We will propose two case studies, illustrating at the same time the possibilities of exploiting the Hyperdeep software: a study of intertextuality (Ovid) and an attempt to date some letters written by Peter Damian.