System and method for machine learning based QoE prediction of voice/video services in wireless networks
US10963803B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 6, 2018 |
| Grant date | Mar 30, 2021 |
| Priority date | — |
| Expiry date | Sep 8, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L43/087
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A framework system and method for developing hybrid voice/video QoE predictors, which use both network/codec/client parameters as well as the voice/video reference sample(s). The prediction model/algorithm uses deep packet inspection to produce relevant input and therefore the network's impact on the voice/video QoE can be determined without recording actual media (voice/video) content. Therefore, the QoE predictors are neither solely media based as available perceptual metrics, nor available parametric based. The present hybrid voice/video QoE uses the reference/original media information, unlike prior art hybrid video only QoE which use the recorded media (video only).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.