Localising speech, footsteps and other sounds using resource-constrained devices

While a number of acoustic localisation systems have been proposed over the last few decades, these have typically either relied on expensive dedicated microphone arrays and workstation-class processing, or have been developed to detect a very specific type of sound in a particular scenario. However, as people live and work indoors, they generate a wide variety of sounds as they interact and move about. These human-generated sounds can be used to infer the positions of people, without requiring them to wear trackable tags. In this paper, we take a practical yet general approach to localising a number of human-generated sounds. Drawing from signal processing literature, we identify methods for resource-constrained devices in a sensor network to detect, classify and locate acoustic events such as speech, footsteps and objects being placed onto tables. We evaluate the classification and time-of-arrival estimation algorithms using a data set of human-generated sounds we captured with se...

• Type: Journal
• Year: 2011
• Where: IPSN
• Authors: Yukang Guo, Mike Hazas
• Keywords: Estimation Algorithms, IPSN 2011, Microphone Arrays, Problem Complexity, Sensor Networks