AmbientSense: A Real-Time Ambient Sound Recognition System for Smartphones

Publication Type Conference Paper
Authors Mirco Rossi, Sebastian Feese, Oliver Amft, Nils Braune, Sandro Martis, Gerhard Tröster
Title AmbientSense: A Real-Time Ambient Sound Recognition System for Smartphones
Abstract This paper presents design, implementation, and evaluation of AmbientSense, a real-time ambient sound recognition system on a smartphone. AmbientSense continuously recognizes user context by analyzing ambient sounds sampled from a smartphone's microphone. The phone provides a user with realtime feedback on recognised context. AmbientSense is implemented as an Android app and works in two modes: in autonomous mode processing is performed on the smartphone only. In server mode recognition is done by transmitting audio features to a server and receiving classification results back. We evaluated both modes in a set of 23 daily life ambient sound classes and describe recognition performance, phone CPU load, and recognition delay. The application runs with a fully charged battery up to 13.75 h on a Samsung Galaxy SII smartphone and up to 12.87 h on a Google Nexus One phone. Runtime and CPU load were similar for autonomous and server modes.
Date 2013
Proceedings Title PerMoby 2013: Proceedings of the International Workshop on the Impact of Human Mobility in Pervasive Systems and Applications
Publisher IEEE
Pages 230–235
DOI 10.1109/PerComW.2013.6529487
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Friedrich-Alexander-Universität Erlangen-Nürnberg