  Snoring is a common disorder that affects people's social and marital lives.
The annoyance caused by snoring can be partially solved with active noise
control systems. In this context, the present work aims at introducing an
enhanced system based on the use of a convolutional recurrent neural network
for snoring activity detection and a delayless subband approach for active
snoring cancellation. Thanks to several experiments conducted using real
snoring signals, this work shows that the active snoring cancellation system
achieves better performance when the snoring activity detection stage is turned
on, demonstrating the beneficial effect of a preliminary snoring detection
stage in the perspective of snoring cancellation.

Audio and Speech Processing