G-g-go! Juuump! Online Performance of a Multi-keyword Spotter in a Real-time Game

Authors

Jill F. Lehman (Disney Research Pittsburgh)
Nikolas Wolfe (Disney Research Pittsburgh)
André Pereira (Disney Research Pittsburgh)

WOCCI 2016

September 5, 2016

G-g-go! Juuump! Online Performance of a Multi-keyword Spotter in a Real-time Game-Image

Two participants playing Mole Madness (left) and a screenshot from the game (right).

We report results for an online multi-keyword spotter in a game that contains overlapping speech, off-task side talk, and keyword forms that vary in completeness and duration. The spotter trained on a data set of 62 children, and expectations for online performance were established by 10-fold cross-validation on that corpus. We compare the post hoc data to the recognizer’s performance online in a study in which 24 new children played with the real-time system. The online system showed a non-significant decline in accuracy which could be traced to trouble understanding the jump keyword and the predominance of younger children in the new cohort. However, children adjusted their behavior to compensate, and the overall performance and responsiveness of the online system resulted in engaging and enjoyable gameplay.

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