Patents Assigned to InfoVista Sweden AB
  • System and Method for Machine Learning Based QoE Prediction of Voice/Video Services in Wireless Networks
    Publication number: 20210150393
    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).
    Type: Application
    Filed: January 22, 2021
    Publication date: May 20, 2021
    Applicant: InfoVista Sweden AB
    Inventors: Per Johansson, Irina Cotanis
  • System and method for machine learning based QoE prediction of voice/video services in wireless networks
    Patent number: 10963803
    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).
    Type: Grant
    Filed: September 6, 2018
    Date of Patent: March 30, 2021
    Assignee: InfoVista Sweden AB
    Inventors: Per Johansson, Irina Cotanis
  • SYSTEM AND METHOD FOR MACHINE LEARNING BASED QoE PREDICTION OF VOICE/VIDEO SERVICES IN WIRELESS NETWORKS
    Publication number: 20190073603
    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).
    Type: Application
    Filed: September 6, 2018
    Publication date: March 7, 2019
    Applicant: InfoVista Sweden AB
    Inventors: PER JOHANSSON, Irina COTANIS