2 citations · 3 across the 4 of their papers we have counts for
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eess.AS2020
On Front-end Gain Invariant Modeling for Wake Word Spotting
Yixin Gao, Noah D. Stein, Chieh-Chi Kao +4
Wake word (WW) spotting is challenging in far-field due to the complexities and variations in acoustic conditions and the environmental interference in signal transmission. A suite…
eess.AS2020★ 1 cited
Towards Data-efficient Modeling for Wake Word Spotting
Yixin Gao, Yuriy Mishchenko, Anish Shah +2
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. Traditional WW mod…
eess.AS2019★ 2 cited
Sub-band Convolutional Neural Networks for Small-footprint Spoken Term Classification
Chieh-Chi Kao, Ming Sun, Yixin Gao +2
This paper proposes a Sub-band Convolutional Neural Network for spoken term classification. Convolutional neural networks (CNNs) have proven to be very effective in acoustic applic…