AmbientSense:用于智能手机的实时环境声音识别系统

2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops) Pub Date : 2013-03-18 DOI:10.1109/PerComW.2013.6529487

M. Rossi, S. Feese, O. Amft, Nils Braune, S. Martis, G. Tröster

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引用次数: 71

摘要

本文介绍了智能手机上的实时环境声音识别系统AmbientSense的设计、实现和评估。AmbientSense通过分析从智能手机麦克风采样的环境声音，持续识别用户环境。该手机为用户提供识别上下文的实时反馈。AmbientSense作为Android应用程序实现，并在两种模式下工作:在自主模式下，仅在智能手机上执行处理。在服务器模式下，识别是通过向服务器发送音频特征并接收分类结果来完成的。我们在一组23个日常生活环境声音类别中评估了这两种模式，并描述了识别性能、手机CPU负载和识别延迟。在充满电的情况下，这款应用在三星Galaxy SII智能手机上可以运行13.75小时，在谷歌Nexus One手机上可以运行12.87小时。自主模式和服务器模式的运行时和CPU负载相似。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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AmbientSense: A real-time ambient sound recognition system for smartphones

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.

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2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)

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