DAGA 2010 - Deutsche Gesellschaft für Akustik eV

154 DAGA 2010 Programm
Mi. 14:50 Grashof C 20 Signalverarbeitung
Cepstral Modulation Features for Classifying Audio Data
A. Nagathil und R. Martin
Ruhr-Universität Bochum, Inst. f. Kommunikationsakustik
A variety of static short-time features derived from different signal domains
such as the time, frequency and cepstral domain has been proposed
for the task of general audio and music classification within the
last decade. Further, the importance of modeling the temporal evolution
of audio signals for improving the classification performance was
demonstrated in the literature. These methods, however, are often based
on the static features which only give a rough description of the
underlying signal. Therefore, we propose an alternative way of feature
extraction in which we first represent the signal dynamics by means of a
highly-resolved cepstral modulation spectrum based on which dynamic
features are extracted for general audio and music classification. For
discriminating speech, music and noise we obtain an average detection
rate of 96%. Musical genres are classified correctly with an accuracy of
81%.
Mi. 15:15 Grashof C 20 Signalverarbeitung
Direction-of-arrival estimation using auditory models employing
pitch analysis
M. Klein-Hennig, M. Dietz, S. Ewert und V. Hohmann
Medizinische Physik, Carl-von-Ossietzky Universität Oldenburg
For the estimation of the direction-of-arrival (DOA) of sounds from binaural
signals, a computational algorithm based on a binaural auditory
model was presented by Dietz et al. [NAG/DAGA, 1299-1300 (2009)].
In the present study, an extension of this DOA estimator with an algorithm
for multiple source tracking based on particle filters [e.g., Särkkä
et al., Information Fusion 8(1), 2-15 (2007)] is suggested and evaluated.
The extended DOA estimator was able to successfully track independent
movements of three concurrent speakers in the frontal, horizontal halfplane
of a virtual acoustic space. To further improve the accuracy and
robustness of speech source tracking and to simulate grouping mechanisms
as employed by the human auditory system, a second extension
of the model by an auditory-model-based pitch (fundamental frequency)
estimator was investigated. The pitch estimator combines spectral and
temporal information of the signal extracted from the excitation pattern
and extracted by strobed temporal averaging, respectively.