We report an experiment with an acoustic surveillance system comprised of a computer and microphone situated in a typical office environment. The system continuously analyzes the acoustic activity at the recording site, separates all interesting events, and stores them in a database. All interesting acoustic events over a duration of more than two months were recorded. A number of low-level signal features are computed from the audio signal and used to classify and identify sound events. The analysis reveals interesting patterns and activities which would be difficult to find by any other means.

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