User Guide
10 TEMS
™
AUTOMATIC 8.1
VSQI
Video Streaming Quality Index is a non-reference method for video
streaming quality assessment. VSQI is based on the quality of the encoded
(compressed) signal prior to transmission, the amount of initial delay, and
the subsequent interruptions during playback of the video sequence: that
is, the time required for initial buffering and the incidence of rebuffering. It
also takes into account the amount of packet loss at the application level
(in other words, in the video streaming client). VSQI is expressed in the MOS
scale.
VTQI
Video Telephony Quality Index is a non-reference method for assessing
the quality of video telephony calls. VTQI is based chiefly on the block error
rate (BLER) measured during the call, while also considering the quality of
the signal prior to transmission. The VTQI score is expressed as a value in
the MOS scale.
Speech quality
TEMS Automatic offers functionality for advanced speech quality as-
sessment. The Perceptual Evaluation of Speech Quality (PESQ) and Speech
Quality Index (SQI) are two of the most important parameters when checking
voice quality. These parameters can be compared with each other, which
greatly facilitates quality evaluation analysis by giving a more complete view
of speech quality, as well as making it possible to conclude if a problem is in
the fixed or mobile network.
PESQ
PESQ is an objective algorithm used for end-to-end speech quality
assessment. It is the ITU-T P.862.1 standard algorithm for measuring speech
quality, providing scores calibrated to the MOS scale. In addition, TEMS
Automatic includes frequent Audio Quality Measurements (AQM), an objec-
tive speech quality score derived from the PESQ algorithm. An advanced
algorithm, AQM gives quality scores with twice the frequency of PESQ. This
makes it easier to geographically pinpoint speech quality problems and to
find the corresponding radio problem. TEMS Automatic also verifies volume,
echo, and silent as part of the PESQ measurements.
TEMS Automatic provides theability to:
▪ Improve QoS
– By reporting quality trends that show
the impact of optimization efforts on a
daily, weekly, or monthly basis.
– By providing continuous feedback on
the Quality of Service of the live
network as experienced by subscribers,
in regards to both speech quality and
data services.
▪ Reduce churn and increase revenue
– By detecting faults, capacity bottle-
necks, and configuration problems
immediately – before subscribers do.
▪ Reduce costs
– By allowing field engineers to focus on
planning, troubleshooting, and fixing
errors rather than merely collecting
data.
– By minimizing the time it takes to
create and distribute quality reports.