A Multi-Party Dialogue Ressource in French
This provides a domain-specific resource for French NLP researchers, but it is incremental as it adapts existing methods to new data.
The authors introduced DinG, a corpus of transcribed multi-party French dialogues from board game sessions, to provide a resource for studying dialogue structure and question types, aiming to improve automatic dialogue systems.
We present Dialogues in Games (DinG), a corpus of manual transcriptions of real-life, oral, spontaneous multi-party dialogues between French-speaking players of the board game Catan. Our objective is to make available a quality resource for French, composed of long dialogues, to facilitate their study in the style of (Asher et al., 2016). In a general dialogue setting, participants share personal information, which makes it impossible to disseminate the resource freely and openly. In DinG, the attention of the participants is focused on the game, which prevents them from talking about themselves. In addition, we are conducting a study on the nature of the questions in dialogue, through annotation (Cruz Blandon et al., 2019), in order to develop more natural automatic dialogue systems.