30 citations · 31 across the 2 of their papers we have counts for
2 papers
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.AS2020★ 30 cited
Accurate Detection of Wake Word Start and End Using a CNN
Christin Jose, Yuriy Mishchenko, Thibaud Senechal +3
Small footprint embedded devices require keyword spotters (KWS) with small model size and detection latency for enabling voice assistants. Such a keyword is often referred to as \t…