Using Pesq - OPTICOM OPERA - V 3.5 User Manual

C H A P T E R 6 :
Clipping. HOT can be assessed by a frequency analysis of the received signal.
As long as the reference sine tone is detected in the received signal, the VAD is
open. Once it is closed, the decoder should generate comfort noise. The major
problems with this algorithm are:
•
The special test sequence used by this method is almost ideal for a
VAD device, and the switching points between voice and silence
are much easier to detect than with real speech.
•
Inaccurate measurement of FEC if a delay variation or drop out
occurs during the noise pulse.
•
Transmission of a pure sine tone may be critical on some networks.
Correlation of the spectra
Another method is to correlate the spectra of the reference signal and the
received test signal. This allows for a very accurate detection of HOT. However,
the temporal resolution is limited to the FFT window size. A shorter window
allows for a higher resolution, but the correlation results will become less
reliable. This method can work with real speech signals.
Ideal VAD plus Time Alignment
This method is used in OPERA. It takes the time aligned signals from PESQ,
realigns them if required and calculates an almost ideal VAD on both signals. It
is much easier for the measurement algorithm to calculate a VAD than for the
codec, since no realtime criteria have to be met. Likewise, the measurement
algorithm has no restrictions in terms of latency, which means that it can
analyse the entire signal before deciding which parts are active speech and
which parts are silence. This method can also be used for real voice.
Dropouts are parts of the test signal, where the signal contains little or no
energy, while there is energy in the reference signal. Dropouts are mostly
caused by packet loss in IP networks, or severe RF problems in mobile
networks. Using OPERA you can identify dropouts in the signal and analyse
them graphically. Dropouts are shown in the same diagram as the VAD
parameters.

6.6.3 Using PESQ

In general usage of the PESQ algorithm is exactly the same as using the PSQM
algorithm. However there are a few significant differences:
•
PESQ has no algorithm specific settings
•
Since the ITU recommendation P.862 / PESQ is much more specific than
PSQM was, and includes a really good time alignment algorithm, most of
the settings for the signal preprocessing are disabled. OPERA uses exactly
the parameters that are defined by the standard.
T E L E P H O N Y B A N D
T E S T I N G
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V O I C E Q U A L I T Y
Drop outs