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Carleton University

Single-ended non-intrusive speech quality monitoring in VoIP

Abstract

dc:description.abstract

Voice over Internet Protocol (VoIP) is a promising technology and it is expected to replace the traditional telephone networks in the next few years. However, speech quality in VoIP is not guaranteed, due to various new impairments introduced by Internet and Internet Protocol (IP) terminals. Evaluating VoIP speech quality in a non-intrusive fashion is challenging, as a reference signal is not accessible.The thesis develops a single-ended, non-intrusive speech quality classification and assessment algorithm in VoIP, which reflects end-users’ true quality of experience. A novel assessment structure is proposed, which utilizes a three-step strategy: impairment detection, individual effect modeling and an overall assessment model. The algorithm combines the merits of voice payload and IP header analysis approaches, and several major impairments in VoIP, including temporal clipping, echo, packet loss and noise, are investigated in the thesis.To model the effects of temporal clipping on speech quality, an algorithm based on the clipping statistics is developed, with different weighting factors assigned to different clipping locations. For the effects of packet loss, a scheme is proposed to first classify the lost packet into three types: silence, unvoiced and voiced, then an algorithm is developed by using loss localization information. To reflect the effects of loss burstiness, a new codec-dependent parameter is introduced. Two prevailing VoIP codecs, ITU-T Rec. G.711 and G.729A, are examined. Echo detection is achieved by measuring its echo path delay and echo path loss. Two algorithms suitable for VoIP scenarios where echo delay is excessive and echo path is nonlinear are developed. For the overall model, the individual models for temporal clipping and packet loss are first combined, with the noise and echo perception models in the E-model, an overall assessment model is developed. Particularly, a two-step noise power estimation method is adopted. The noise additivity assumption in the E-model is examined and a correction curve is suggested.In the thesis, ITU-T Ree. P.862.1 is used to objectively measure the speech quality. The simulation results show the accuracy and effectiveness of the proposed algorithm. The correlation between prediction and measurement is 0.90, and standard error is 0.27 Mean Opinion Score (MOS). A subjective MOS test covering some key scenarios is also conducted; the ratings are analyzed to verify the novel concepts and to calibrate the proposed models. Moreover, the performance limitations of several leading objective measures are pointed out.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (Ph.D.)
Level thesis:degree_level
Doctoral
Discipline thesis:degree_discipline
Engineering, Electrical
Grantor dc:publisher
Carleton University
Year dc:date.issued
2007

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ding, Lijing

Rights

dc:rights
Statement dc:rights
  • Copyright © 2007 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
Language dc:language.iso
en

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:carleton.scholaris.ca:20.500.14718/32086

Chain of custody

source
Harvested from
Carleton University
Base URL
carleton.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
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citation

Ding, Lijing. Single-ended non-intrusive speech quality monitoring in VoIP. Doctoral thesis, Carleton University, 2007. https://hdl.handle.net/20.500.14718/32086