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Multi-party Language Interaction in a Fast-Paced Game Using Multi-keyword Spotting

机译:使用多关键字发现的快节奏游戏中的多方语言交互

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Existing speech technology tends to be poorly suited for young children at play, both because of their age-specific pronunciation and because they tend to play together, making overlapping speech and side discussions about the play itself ubiquitous. We report the performance of an autonomous, multi-keyword spotter that has been trained and tested on data from a multi-player game designed to focus on these issues. In Mole Madness, children laugh, yell, speak at the same time, make side comments and even invent their own forms of keywords to control a virtual on-screen character. Within this challenging language environment, the system achieves 94% overall recall and 85% overall accuracy, providing child-child and child-robot pairs with responsive play in a rapid-paced game. This technology can enable others to create novel multi-party interactions for entertainment where a limited number of keywords has to be recognized.
机译:现有的语音技术由于其特定年龄的发音以及由于他们倾向于一起玩耍,因此不大适合在游戏中的幼儿,这使得重叠的语音和关于游戏本身的讨论无处不在。我们报告了一个自主的多关键字点检器的性能,该点标器已针对来自专门针对这些问题的多玩家游戏中的数据进行了培训和测试。在《疯狂的摩尔》中,孩子们同时大笑,大喊,说话,发表旁注,甚至发明自己的关键字形式来控制虚拟的屏幕角色。在这种充满挑战的语言环境中,该系统可实现94%的整体召回率和85%的整体准确性,从而在快速节奏的游戏中为儿童对儿童和机器人对提供响应性游戏。这项技术可以使其他人创建新颖的多方互动来进行娱乐活动,其中必须识别数量有限的关键字。

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