artificial text COrpus DEsIgNed Ethically : automatic synthesis of clinical documents

Machine learning methods have become prevalent in language technologies. They rely on annotated corpora to train and evaluate models. The CoDeinE project proposes to address the lack of shareable corpora in sensitive domains such as health or banking. The key idea of the project is to define methods for paraphrase generation and apply them to confidential corpora to automatically generate synthetic texts that mimic the linguistic properties of real documents while preserving confidentiality. The project addresses important issues in natural language processing and is also concerned with defining confidentiality criteria to ensure that no original confidential information is found in the generated synthetic texts. We will use clinical documents in electronic patient records as a case study. Furthermore, the project will rely on Games With A Purpose and crowd sourcing to validate and annotate the synthesized texts.