Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems 2014
DOI: 10.1145/2668332.2668349
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DSP.Ear

Abstract: The rapidly growing adoption of sensor-enabled smartphones has greatly fueled the proliferation of applications that use phone sensors to monitor user behavior. A central sensor among these is the microphone which enables, for instance, the detection of valence in speech, or the identification of speakers. Deploying multiple of these applications on a mobile device to continuously monitor the audio environment allows for the acquisition of a diverse range of sound-related contextual inferences. However, the cu… Show more

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Cited by 40 publications
(2 citation statements)
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References 30 publications
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“…In [29], Hao et al developed iSleep that detects and recognizes sounds of body movement, coughing and snoring to infer sleep quality. In [30], Georgiev et al developed DSP.Ear that recognized stress and emotion (amongst others) via the microphone using only the DSP of a smartphone. In [31], Nirjon et al developed MusicalHeart that integrated a microphone into an earphone to extract heartbeat information from audio signals.…”
Section: Related Workmentioning
confidence: 99%
“…In [29], Hao et al developed iSleep that detects and recognizes sounds of body movement, coughing and snoring to infer sleep quality. In [30], Georgiev et al developed DSP.Ear that recognized stress and emotion (amongst others) via the microphone using only the DSP of a smartphone. In [31], Nirjon et al developed MusicalHeart that integrated a microphone into an earphone to extract heartbeat information from audio signals.…”
Section: Related Workmentioning
confidence: 99%
“…In [78] the authors propose an integrated sensing system to perform complex and simultaneous audio inferences. This system is used to monitor the user behaviour by continuously capturing the audio environment.…”
Section: Using Sensor Data To Monitor Behaviourmentioning
confidence: 99%