New Models for Perceived Voice Quality Prediction and their Applications in Playout Buffer Optimization for VoIP Networks University of Plymouth United Kingdom {L.Sun; Dr. Lingfen Sun Prof Emmanuel Ifeachor
ICC 2004, Paris France, June Outline Background Speech quality for VoIP networks Current status Aims of the project Main Contributions Novel non-intrusive voice quality prediction models Novel perceptual-based speech quality optimization (e.g. jitter buffer optimization) mechanism Conclusions and Future Work
ICC 2004, Paris France, June Background – Speech Quality for VoIP Networks VoIP speech quality: end-user perceived quality (MOS), an important metric. Affected by IP network impairments and other impairments. Voice quality measurement: subjective (MOS ) or objective (intrusive or non-intrusive) SCN IP Network Gateway SCN: Switched Comm. Networks (PSTN, ISDN, GSM …) End-to-end Perceived speech quality Intrusive measurement Non-intrusive measurement MOS Reference speech Degraded speech
ICC 2004, Paris France, June Current Status and Problems Lack of an efficient non-intrusive speech quality measurement method E-model (a complicated computational model) Based on subjective tests to derive models/parameters, time- consuming and expensive. Only limited models exist Lack of perceptual optimization control methods only based on individual network parameters for buffer optimization and QoS control purposes not perceptual-based optimization control
ICC 2004, Paris France, June Aims of the Project IP Network Receiver Voice source Voice receiver Encoder Sender Packetizer Jitter buffer Decoder De- packetizer Non-intrusive measurement MOS End-to-end perceived voice quality (MOS) To develop novel and efficient method/models for non-intrusive quality prediction, To apply the models for perceptual-based optimization control ( e.g. buffer optimization or adaptive sender-bit-rate QoS control).
ICC 2004, Paris France, June Novel Non-intrusive Voice Quality Prediction Based on intrusive quality measurement (e.g. PESQ) to predict voice quality non-intrusively which avoids subjective tests. A generic method which can be applied to audio, image and video. VoIP Network New model (packet loss, delay, codec …) Predicted MOSc PESQ E-model Measured MOSc delay MOS(PESQ) Reference speech Degraded speech Intrusive method (regression or ANN models) Non-intrusive method
ICC 2004, Paris France, June New Structure to Obtain MOS c PESQ can only predict one-way listening speech quality (expressed as MOS). By a new combined PESQ/E-model structure, a conversational speech quality (MOSc) can be obtained as Measured MOSc. PESQ Delay model MOS R I e IeIe End-to-end delay E-model MOSc IdId Reference speech Degraded speech MOS (PESQ)
ICC 2004, Paris France, June Regression based Models (1) Nonlinear regression models are derived for I e based on PESQ/PESQ-LQ Further combine I e with I d to obtain MOS c. MOS (PESQ) I e model IeIe E-model MOSc I d model IdId Delay (d) Codec Packet loss Reference speech Degraded speech Speech database Encoder Loss model Decoder Nonlinear regression model (I e model) Predicted I e PESQ/ PESQ-LQ MOS R I e Measured I e (a) (b)
ICC 2004, Paris France, June Regression based Models (2) I e can be modelled by a logarithm fitting function with the form of Parameters for different codecs (PESQ) ParametersAMR(H)AMR(L)G.729G.723.1iLBC a b* c
ICC 2004, Paris France, June Regression Models for AMR (12.2Kb/s) e.g. for AMR (12.2Kb/s), The goodness of fit is: SSE = 2.83 and R 2 = MOS vs. packet loss and delay
ICC 2004, Paris France, June Perceptual-based Buffer Optimization Motivation: only based on individual network parameters (e.g. delay or loss) targeting only minimum average delay or minimum late arrival loss, not maximum MOS. There is a need to design buffer algorithm to achieve optimum perceived speech quality. Contribution A perceptual-based optimization jitter buffer algorithm o Use regression based models for buffer optimization o Use a minimum impairment criterion instead of traditional maximum MOS score o A Weibull delay distribution based on trace analysis o A perceptual-based optimization of playout buffer algorithm
ICC 2004, Paris France, June Impairment Function I m Define: impairment function I m Playout delay d Weilbull distribution buffer loss b
ICC 2004, Paris France, June Minimum Impairment Criterion Define: minimum impairment criterion Given:network delay d n, network loss n and codec type Estimate: an optimized playout delay d opt Such that: minimize I m can be reached. d 1 d 2 d 3 d 4 Minimum I m
ICC 2004, Paris France, June Perceptual-based Optimization Buffer Algorithm For every packet i received, calculate network delay n i If mode == SPIKE then if n i tail*old_d then mode = NORMAL elseif n i > head*d i then mode = SPIKE; old_d = d i else -update delay records for the past W packets endif At the beginning of a talkspurt If mode == SPIKE then d i = n i else -obtain ( , , ) for Weilbull distribution for the past W packets -search playout d which meets minimum I m criterion endif
ICC 2004, Paris France, June Performance Analysis and Comparison (1) Selected five traces from UoP to CU (USA), DUT (Germany), BUPT (China), and NC (China). Traces 1 and 3 with high delay variation and traces 2, 4, 5 with low delay variation TraceDelay (ms) Jitter (ms) Loss (%)
ICC 2004, Paris France, June Performance Analysis and Comparison (2) “p-optimum” algorithm achieves the optimum voice quality for all traces. “adaptive” algorithm achieves sub-optimum quality with low complexity.
ICC 2004, Paris France, June Conclusions and Future Work Conclusions The development of a new methodology and regression models to predict voice quality non-intrusively. Demonstrated the application of new non-intrusive voice quality prediction models to perceptual-based optimization of playout buffer algorithms. Future Work To consider buffer adaptation during a talkspurt in order to achieve the best trade-off between delay, loss and end-to-end jitter. To extend the work to improve the performance of multimedia services (e.g. audio/image/video) over IP networks
ICC 2004, Paris France, June Contact Details Dr. Lingfen Sun Prof Emmanuel Ifeachor Any questions? Thank you!