In This Section
Perceptual Effects of Dynamic Range Compression in Popular Music Recordings - January 2014
Accurate Calculation of Radiation and Diffraction from Loudspeaker Enclosures at Low Frequency - June 2013
New Measurement Techniques for Portable Listening Devices: Technical Report - October 2013
AES Journal Forum
Acoustic Detection of Human Activities in Natural Environments
Automatic recognition of sound events can be valuable for efficient analysis of audio scenes. For example, detecting human activities like trespassing and hunting in natural environments can play an important role in their preservation by alerting authorities to take action. In the proposed system, each sound class is represented by a hidden Markov model created from descriptors in the time, frequency, and wavelet domains. The system has the ability to automatically adapt to acoustic conditions of different scenes via the feedback loop that refines an unsupervised model. A reliable testing process was adopted for assessing the performance of the system under adverse conditions characterized by highly nonstationary environmental noise.
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