Home monitoring for frailty detection through sound and speaker diarization analysis

TL;DR

This paper explores advanced sound processing and speaker diarization techniques to enhance home monitoring systems for detecting frailty among aging populations, emphasizing privacy and reliability.

Contribution

It introduces two new methods for speaker diarization and demonstrates how DNN-based approaches significantly improve performance in home monitoring applications.

Findings

DNN-based approaches double diarization accuracy

Two new methods outperform existing techniques

Enhanced privacy-preserving monitoring system

Abstract

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%.