<anchor xmlns="http://www.tei-c.org/ns/1.0" xml:id="id_docs-internal-guid-68b34743-f5d0-46e7-1731-31344ad11bf6" />In this paper, we introduced a neural network architecture that is able to learn the classification of direct speech by training on weakly labelled data. This network works purely on the raw text of a novel by taking into account a relatively large context. We also demonstrate that training on weakly labelled data leads to satisfying results.