Let’s Play videos — which document game playthroughs — have surged in popularity in the past decade. Felix Kjellberg, better known by his online pseudonym PewDiePie, now reaches over 100 million subscribers on YouTube with his Let’s Play content. And a recent report estimates that the audience for Let’s Play videos and livestreams now rivals that of paid content from HBO, Netflix, ESPN, and Hulu combined.
But producing quality Let’s Play videos takes time, much of which is devoted to writing scripts. To ease the burden on creators, a team at the Georgia Institute of Technology and the University of Alberta recently investigated an AI system that can automatically generate commentary. They say their approach outperforms existing work and lays the groundwork for future studies.
“Let’s Plays of video games represent a relatively unexplored area for experimental AI in games … There are a number of reasons why Let’s Plays may be of interest to Game AI researchers,” explained the paper’s coauthors. “First, part of Let’s Play commentary focuses on explaining the game, which is relevant to game tutorial generation, gameplay commentary, and explainable AI in games broadly. Second, Let’s Plays focus on presenting engaging commentary. Thus if we can replicate Let’s Play commentary, we may be able to extend such work to improve NPC dialogue and system prompts. Finally, Let’s Plays are important cultural artifacts, as they are the primary way many people engage with video games.”
An AI architecture commonly applied to analyzing visual imagery served as the system’s framework: a convolutional neural network (CNN). Three 25-minute YouTube videos were collected — one each from three popular Minecraft Let’s Play channels — and their associated transcripts were extracted to build a commentary corpus. See more at Venture Beat.