Examination of Firearms Review: 2007 to 2010 - Interpol

In June of 2010, Michael Jessen of the BKA presented Current developments in
forensic speaker identification at Odyssey 2010: The Speaker and Language
Recognition Workshop. That presentation contains a wealth of information that may be
useful to speaker identification practitioners.
4. Audio Enhancement, Related Audio Fields, Laboratory Procedures and
Working Groups (Carl Kriigel)
To improve the intelligibility of speech it is necessary to suppress or attenuate the
unwanted noise that occurs in audio recordings. Ellwart and Czyzewski (48) propose
an algorithm that is based on a combination of adaptive filtration and spectral
subtraction to reduce noise and improve the speech quality. The method utilizes two
signals: the sound recorded by the microphone containing the speech including noise
and the second signal containing only the noise. Several experiments were conducted
using microphones with different characteristics. The results indicate the method
worked well in various environmental conditions. Bitzer and Brandt (49) investigated
the weakness of standard noise reduction approaches and offered solutions for burst
from GSM (Global System Mobile Communication). One method for GSM burst
removal, suggested by Bitzer and Brandt, utilized a template signal cancellation. The
approach is to build a template of the burst signal and apply it over all detected bursts to
remove the GSM. Bitzer and Brandt discussed other approaches to speech
enhancement and limitations (such as low grade microphones, A/D converters and
compression/coding algorithms).
There are several manufacturers of commercial noise-reduction systems that contain a
wide range of parameters that have to be adjusted by the forensic practitioners. These
adjustments are opinion settings based on the practitioners’ experience and training but
may not produce optimal results. Hilkhuysen and Huckvale (50) studied the differences
between opinion based operator settings and settings using an intelligibility model.
The intelligibility model is founded on a speech envelope distortion measure to predict
optimal parameter settings of commercial noise-reduction systems. Hilkhuysen and
Huckvale’s results indicate that the intelligibility model is able to predict optimal
parameter settings better than human operators, even though the model contains
imperfections.
Audio restoration software in forensic applications has raised some questions regarding
the validity of investigative and legal recordings. Koenig and Lacey (51) tested two
widely available software programs using both speech information and sine waves. The
results of the restoration were compared to the original source clip recording using a
386