PASTEL is a research project that aims to explore the potential of real time and automatic transcriptions for the instrumentation of mixed educational situations where the modalities of the interactions can be face-to-face or online, synchronous or asynchronous. The speech recognition technology approaches a maturity level that allows new opportunities of instrumentation in pedagogical practices and their new uses.

More specifically, we develop (1) a real-time transcription application, and (2) educational outreach applications based on the transcription system outputs. These results will be used to automatically generate the materials of a basic SPOC. A set of editing features will be implemented for the mentioned applications that will allow the teacher to adapt and customize these contents according to their needs. Then, the developed applications will be made available to public institutions for higher education and research, and will also be transferred to the industry through Orange or start-ups associated to he research laboratories involved in the project.

The major innovations of PASTEL cover the discourse structure from automatic transcriptions that are linked to its educational objectives. The innovation also features the challenging flow processing in real time, which is required when the discourse structure is being used in a face-to-face situation. The project also brings innovative solutions in terms of instrumentation, and diversification of pedagogical practices, as well as a new approach to design and structure online educational contents, based on the use of speech recognition technology.