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Characterizing Language Use in a Collaborative Situated Game

Published: December 3, 2025 | arXiv ID: 2512.03381v2

By: Nicholas Tomlin , Naitian Zhou , Eve Fleisig and more

Potential Business Impact:

Helps people learn to talk better playing games.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

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.

Page Count
27 pages

Category
Computer Science:
Computation and Language