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SoundSense: Scalable Sound Sensing for People-Centric Applications on Mobile Phones
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BibTeX
@MISC{Lu_soundsense:scalable,
author = {Hong Lu and Wei Pan and Nicholas D. Lane and Tanzeem Choudhury and Andrew T. Campbell},
title = {SoundSense: Scalable Sound Sensing for People-Centric Applications on Mobile Phones},
year = {}
}
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Abstract
Top end mobile phones include a number of specialized (e.g., accelerometer, compass, GPS) and general purpose sensors (e.g., microphone, camera) that enable new people-centric sensing applications. Perhaps the most ubiquitous and unexploited sensor on mobile phones is the microphone – a powerful sensor that is capable of making sophisticated inferences about human activity, location, and social events from sound. In this paper, we exploit this untapped sensor not in the context of human communications but as an enabler of new sensing applications. We propose SoundSense, a scalable framework for modeling sound events on mobile phones. SoundSense is implemented on the Apple iPhone and represents the first general purpose sound sensing system specifically designed to work on resource limited phones. The architecture and algorithms are designed for scalability and SoundSense uses a combination of supervised and unsupervised learning techniques to classify both general sound types (e.g., music, voice) and discover novel sound events specific to individual users. The system runs solely on the mobile phone with no back-end interactions. Through implementation and evaluation of two proof of concept peoplecentric sensing applications, we demostrate that SoundSense is capable of recognizing meaningful sound events that occur in users ’ everyday lives. Categories and Subject Descriptors
Keyphrases
mobile phone scalable sound sensing people-centric application sound event unexploited sensor human activity top end mobile phone novel sound event subject descriptor human communication enable new people-centric sensing application untapped sensor general sound type user everyday life powerful sensor back-end interaction general purpose sensor individual user meaningful sound event apple iphone concept peoplecentric sensing application sophisticated inference social event scalable framework first general purpose sound
