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

 

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.

September 6, 2016
WOCCI 2016

 

Authors

Jill Fain Lehman (Disney Research)

Nikolas Wolfe (Disney Research)

André Pereira (Disney Research)

 

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

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Abstract

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 was 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 analysis 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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