  Describes an audio dataset of spoken words designed to help train and
evaluate keyword spotting systems. Discusses why this task is an interesting
challenge, and why it requires a specialized dataset that is different from
conventional datasets used for automatic speech recognition of full sentences.
Suggests a methodology for reproducible and comparable accuracy metrics for
this task. Describes how the data was collected and verified, what it contains,
previous versions and properties. Concludes by reporting baseline results of
models trained on this dataset.
