Characterizing Language Use in a Collaborative Situated Game
This work provides a valuable resource for researchers studying language in complex, collaborative scenarios, though it is incremental as it focuses on data collection and analysis without introducing new methods.
The authors tackled the problem of understanding language use in collaborative, situated problem-solving by collecting and analyzing the Portal Dialogue Corpus, which includes 11.5 hours of spoken dialogue and 24.5K utterances from the Portal 2 game, revealing unique linguistic phenomena such as complex spatial reference and ad-hoc convention formation.
Cooperative video games, where multiple participants must coordinate by communicating and reasoning under uncertainty in complex environments, yield a rich source of language data. We collect the Portal Dialogue Corpus: a corpus of 11.5 hours of spoken human dialogue in the co-op mode of the popular Portal 2 virtual puzzle game, comprising 24.5K total utterances. We analyze player language and behavior, identifying a number of linguistic phenomena that rarely appear in most existing chitchat or task-oriented dialogue corpora, including complex spatial reference, clarification and repair, and ad-hoc convention formation. To support future analyses of language use in complex, situated, collaborative problem-solving scenarios, we publicly release the corpus, which comprises player videos, audio, transcripts, game state data, and both manual and automatic annotations of language data.