  As the French, European and worldwide populations are aging, there is a
strong interest for new systems that guarantee a reliable and privacy
preserving home monitoring for frailty prevention. This work is a part of a
global environmental audio analysis system which aims to help identification of
Activities of Daily Life (ADL) through human and everyday life sounds
recognition, speech presence and number of speakers detection. The focus is
made on the number of speakers detection. In this article, we present how
recent advances in sound processing and speaker diarization can improve the
existing embedded systems. We study the performances of two new methods and
discuss the benefits of DNN based approaches which improve performances by
about 100%.
