The Future of Interaction with Mobile Game Characters

被引:0
|
作者
Mendez, Roberto Lopez [1 ]
Li, Sicong [1 ]
Liu, Hong Ji [1 ]
机构
[1] Arm Ltd, Cambridge, England
关键词
user interaction in games; speech-based user interaction; speech recognition; language model; unity ml-agents; mobile games;
D O I
10.1145/3641234.3671019
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This poster showcases the future of player-NPC interaction in gaming: more natural, based on speech. The poster explains the implementation of verbal interaction with an NPC in a mobile game. Large Language Models (LLMs) open new ways of interacting in gaming, but the large size and memory footprint make deploying them on mobile a challenge. We have identified a 33M-parameter small Language Model (LM), TinyStories [Eldan and Li 2023], re-purposed it to be conversational, and combined it with the standard Unity Multi-Layer Perceptron (MLP) ML-Agents [Juliani et al. 2020] model. The LM drives the interaction with the user, while the MLP performs the actions. A Sentence Similarity model [Reimers and Gurevych 2019] is then responsible for filtering user input to decide whether the NPC needs to communicate with the player or to perform an action. Running all these models locally on mobile inside a game engine like Unity can be very challenging in terms of optimization, but this poster demonstrates how it is possible.
引用
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页数:2
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