Abstract
Existing speech technology tends to be poorly suited for young children at play, both because of their age-speci c 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.
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