DAGA 2010 - Deutsche Gesellschaft für Akustik eV

Programm DAGA 2010 157
limited. Averaging may fail due to time variances, particularly outdoors.
Thus we aim to use single block periods and to do the measurement
only once. For improvement of SNR we tried several signal processing
methods. As for the constant surrounding machine’s noises, the timevariant
filter is employed, and wavelet de-noising algorithms is considered.
As for the instantaneous noise, where the frequency range overlaps
with the sweep frequency range unpredictably, microphone arrays and
inter-correlation based de-noising algorithms used in source separation
techniques are also considered. In the presentation some examples and
first solutions are shown and discussed.
Mi. 17:45 Grashof C 20 Signalverarbeitung
Objective quality measures for dereverberation methods based on
room impulse response equalization
E. Albertin, J. Rennies und S. Goetze
Fraunhofer IDMT / Hör-, Sprach- und Audiotechnologie, Oldenburg
Hands-free communication devices are commonly used e.g. in offices
or car environments. These devices have to cope with several problems
such as ambient noise, acoustic echoes and room reverberation. Reverberation
is caused by reflections at room boundaries in closed spaces
and increases with the spatial distance between the loudspeaker and
the near-end user. A high amount of reverberation decreases speech intelligibility
at the position of the near-end speaker. Listening-room compensation
(LRC) can be used to reduce the influence of reverberation on
acoustic signals. However, such algorithms may have an impact on the
perception of the sound quality of the dereverberated signals. In this contribution
the performance of dereverberation algorithms will be analysed.
The evaluation of the sound quality of the dereverberated signals was
done by the subjective listening tests. Additionally, the objective judgement
of the dereverberated signals was accomplished by using different
objective measures that are expected to be able to assess the quality
of the LRC algorithms. The objective measures were classified in two
different classes: measures that are based on the impulse response of
the system and measures that are based on the signals. The results of
the objective and subjective evaluation will be compared by correlation
analysis.