SoundSense: scalable sound sensing for people-centric applications on mobile phones
SoundSense: scalable sound sensing for people-centric applications on mobile phones
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DOI：
10.1145/1555816.1555834
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发表时间：
2009-06
期刊：
影响因子：
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通讯作者：
Hong Lu;Wei Pan;N. Lane;Tanzeem Choudhury;A. Campbell
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文献类型：
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作者：
Hong Lu;Wei Pan;N. Lane;Tanzeem Choudhury;A. Campbell
高端移动电话包括许多专用传感器（例如加速度计、指南针、GPS）和通用传感器（例如麦克风、摄像头），可实现新的以人为中心的传感应用。也许手机上最普遍且尚未被利用的传感器是麦克风——这是一种功能强大的传感器，能够从声音中对人类活动、位置和社交事件做出复杂的推断。在本文中，我们不是在人类通信的背景下利用这种未开发的传感器，而是将其作为新传感应用的推动者。我们提出了 SoundSense，这是一个可扩展的框架，用于对手机上的声音事件进行建模。 SoundSense 在 Apple iPhone 上实现，代表了第一个专门设计用于资源有限的手机的通用声音传感系统。该架构和算法专为可扩展性而设计，Soundsense 使用监督和无监督学习技术的组合来对一般声音类型（例如音乐、语音）进行分类，并发现特定于个人用户的新声音事件。该系统仅在手机上运行，没有后端交互。通过实施和评估两个以人为中心的传感应用的概念验证，我们证明了 SoundSense 能够识别用户日常生活中发生的有意义的声音事件。
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 people-centric sensing applications, we demostrate that SoundSense is capable of recognizing meaningful sound events that occur in users' everyday lives.