Voice over IP performance monitoring
ACM SIGCOMM Computer Communication Review
Towards a multi-modal perceptual model
BT Technology Journal
Synchronized Two-Way Voice Simulation Tool for Internet Phone Performance Analysis and Evaluation
Proceedings of the 9th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
How does it sound? [voice clarity analysis]
IEEE Spectrum
Characterizing the subjective performance of the ITU-T 8 kb/s speech coding algorithm-ITU-T G.729
IEEE Communications Magazine
Integrated management architecture for IP-based networks
IEEE Communications Magazine
Real-time voice over packet-switched networks
IEEE Network: The Magazine of Global Internetworking
A survey of packet loss recovery techniques for streaming audio
IEEE Network: The Magazine of Global Internetworking
Predicting packet loss statistics with hidden Markov models for FEC control
Computer Networks: The International Journal of Computer and Telecommunications Networking
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A simulation-based methodology is developed for analyzing the perceptual quality of voice-over-IP calls as a function of network quality-of-service (QoS) parameters and choices in configuration and implementation. The proposed method combines the use of existing objective voice-quality measurement algorithms, such as the ITU-T P.861 PSQM and P.862 PESQ, and pre-recorded natural or artificial voice reference signals, such as the ITU-T P.50, with the discrete-event simulation of a network QoS model. A significant advantage of the method is that it does not involve the use of human subjects in evaluating subjective voice quality. This enables one to entirely automate the process of quantifying call quality as a function of network QoS and implementation choices such as packet size and codec type. Such automation enables one to realize significant time and cost savings in obtaining experimental results. A tool implementation is described that includes basic network packet loss, delay jitter, and call multiplexing models. Example numerical results are presented. The generalization of the method to the automated perceptual quality evaluation of audio, video, and multimedia signals is also described.