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Beschreibung:
In the modern world, we are increasingly surrounded by computation devices with communication links and one or more microphones. Such devices are, for example, smartphones, tablets, laptops or hearing aids. These devices can work together as nodes in an acoustic sensor network (ASN). Such networks are a growing platform that opens the possibility for many practical applications. ASN based speech enhancement, source localization, and event detection can be applied for teleconferencing, camera control, automation, or assisted living. For this kind of applications, the awareness of auditory objects and their spatial positioning are key properties. In order to provide these two kinds of information, novel methods have been developed in this thesis. Information on the type of auditory objects is provided by a novel real-time sound classification method. Information on the position of human speakers is provided by a novel localization and tracking method. In order to localize with respect to the ASN, the relative arrangement of the sensor nodes has to be known. Therefore, different novel geometry calibration methods were developed. Sound classification The first method addresses the task of identification of auditory objects. A novel application of the bag-of-features (BoF) paradigm on acoustic event classification and detection was introduced. It can be used for event and speech detection as well as for speaker identification. The use of both mel frequency cepstral coefficient (MFCC) and Gammatone frequency cepstral coefficient (GFCC) features improves the classification accuracy. By using soft quantization and introducing supervised training for the BoF model, superior accuracy is achieved. The method generalizes well from limited training data. It is working online and can be computed in a fraction of real-time. By a dedicated training strategy based on a hierarchy of stationarity, the detection of speech in mixtures with noise was realized. This makes the method robust against severe noises levels corrupting the ...