Recommendation ITU-T P.565 provides the output of the framework which is a machine learning
based speech quality prediction model that predicts the impact on the speech quality from the Internet
protocol (IP) transport and underlying transport, as well as the jitter buffer in the end client; thus
providing a network centric view on the speech quality service delivered on mobile packet switched
networks. This is expressed in terms of a mean opinion score-listening quality objective (MOS-LQO)
under the assumption of an otherwise clean transmission, without background noise, automatic gain
control, voice enhancement devices, transcoding, bridging, frequency response, clock drift or any
other impairment not caused by the IP transport and underlying transport. The models according to
this framework use information on the temporal structure of the reference signal to identify the
importance of individual sections of the bitstream with regard to speech quality. These models do not
perform any perceptual analysis of the recorded speech signal.
The framework specifies three modules required for the development of these kinds of metrics: the
databases generator module, the machine learning module, and the validation module for the trained
model. In addition, the database content and the features used by the machine learning algorithm are
described. The framework also provides a large set of test vectors, in the form of error (jitter and packet
loss) patterns files for learning and validation. This Recommendation specifies the minimum required
performance, as well as conditions and requirements for an independent additional validation for
models developed based on the framework. The Recommendation also specifies implementation
requirements.
The models developed based on the framework enable the assessment of transmission network impact
on speech quality for mobile packet-switched voice services, and therefore benefit operators and
regulators alike with a fast and easy speech quality trend monitoring/benchmarking and
troubleshooting. In addition, if predictors according to this framework are used together with
perceptual speech quality metrics like [ITU-T P.863], it is possible to identify if the source of problems
resides inside or outside the transport network observed by the predictor according to this framework.
Consequently, a more detailed analysis of the situation can be achieved and troubleshooting of less
obvious degradations such as the ones occurring outside of the transport network (e.g., emerged from
automatic gain control, voice enhancement devices, transcoding or analogue processing) is enabled.
This Recommendation includes electronic attachments containing detailed descriptions of generic jitter files and a reference speech sample (see Annex F). |
