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Found 3 papers, 1 papers with code
Towards Data-efficient Modeling for Wake Word Spotting
Wake word (WW) spotting is challenging in far-field not only because of the interference in signal transmission but also the complexity in acoustic environments.
Accurate Detection of Wake Word Start and End Using a CNN
In this paper, we propose two new methods for detecting the endpoints of wake words in neural KWS that use single-stage word-level neural networks.
Deep Residual Networks with Exponential Linear Unit
These very deep models have lead to a considerable decrease in test errors, on benchmarks like ImageNet and COCO.
Ranked #143 on
Image Classification
on CIFAR-10
