NDLI: A_PSQA: PESQ-like non-intrusive tool for QoE prediction in VoIP services

Content Provider	IEEE Xplore Digital Library
Author	Cherif, W. Ksentini, A. Negru, D. Sidibe, M.
Copyright Year	2012
Description	Author affiliation: IRISA - University of Rennes 1 - Campus Universitaire de Beaulieu, 35042 Rennes, France (Ksentini, A.) \|\| Viotech Communiction - 12, avenue des Prés, 78180 Montigny le Bretonneux, France (Cherif, W.; Sidibe, M.) \|\| CNRS LaBRI lab., University of Bordeaux - 351, Cours de la Libération, 33405 Talence, France (Negru, D.)
Abstract	Perceived speech quality, or Quality of Experience (QoE), is the key criteria for evaluating VoIP service. Most of the existing solutions are intrusive, in a sense where they require both the original and the transmitted audio sequences. These solutions give good estimation of the QoE, but they cannot be used in real-time. In fact, Service Provider and Network Provider are highly interested on automatic QoE estimation tool (without intrusion) in order to monitor and control the perceived quality of their VoIP service. In this paper, we present a new perceived speech quality estimation tool, named $ALICANTE^{1}$ Pseudo Subjective Quality Assessment (A_PSQA) for two widely VoIP codecs, iLBC and Speex. A_PSQA is a non-intrusive method, which relies on Random Neural Network (RNN) approach to learn the nonlinear relation between network parameters and the perceived user QoE. Furthermore, to avoid costly and time-consuming subjective tests, we used a well-known intrusive method ITU-T's Perceptual Evaluation Quality (PESQ) to estimate the MOS. Obtained results show that A_PSQA is able to estimate the MOS like PESQ, while being non-intrusive. Besides, A_PSQA's results are compared with two non-intrusive (IQX and E-Model) methods, where A_PSQA shows the highest correlation with PESQ estimation than all others methods.
Starting Page	2124
Ending Page	2128
File Size	354950
Page Count	5
File Format	PDF
ISBN	9781457720529
ISSN	15503607
e-ISBN	9781457720536
e-ISBN	9781457720512
DOI	10.1109/ICC.2012.6364004
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-10
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech Codecs Correlation Artificial neural networks Speex Perceived Speech Quality QoE MOS PESQ E-model iLBC
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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