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The Role of Sensory Psychology to VoIP Rate Adaptation : A Study on Skype Calls

Feb 23, 2016




The Role of Sensory Psychology to VoIP Rate Adaptation : A Study on Skype Calls. Skype Group, NSLAB INFOCOMM2012(Hopefully). Tx /Rx Content Bitrate Jitter Packet Loss Rate Quality of Service( QoS ). Mean Opinion Score (MOS) Reaction Time Reactivity/Responsiveness - PowerPoint PPT Presentation

User-centric Adaptation on Multimedia Internet Services

The Role of Sensory Psychology to VoIP Rate Adaptation: A Study on Skype CallsSkype Group, NSLABINFOCOMM2012(Hopefully)Network and Systems

Network and Systems

Network and Systems

Network and Systems

Tx/Rx ContentBitrateJitterPacket Loss RateQuality of Service(QoS)Network and Systems

Network and Systems

Mean Opinion Score (MOS)Reaction TimeReactivity/ResponsivenessQuality of Experience (QoE)

Network and Systems TimeReactivityQoSTx/Rx ContentBitrateJitterPacket Loss

Network and Systems

Network and Systems WorksOn the TCP-Friendliness of VoIP Traffic, Tian Bu et al., INFOCOM2006Disprove the conjecture that VoIP is not TCP-Friendly after taking the user back-off mechanism into account.User back-off: real time appswill drop out completely ifthe user perceived unacceptable quality due tonetwork congestion.

Network and Systems WorksQuantifying Skype User Satisfaction, K. T. Chen et al., SIGCOMM2006The User Satisfaction Index(USI)Using traditional metrics(RTT, jitter, bitrate) to infer user-centric metrics (reactivity, duration, MOS.)Allow real-time and user-centric adaptation .

Network and Systems WorksCould Skype be More Satisfying?, T. Y. Huang et al., IEEE Network 2010Skypes adaptation does not take the individual codec and packet loss patterns into consideration.The inconsistency in voice quality results in over-utilization of bandwidth.

Network and Systems WorksAn Experimental Investigation of the CongestionControl Used by Skype, L. D. Cicco et al., WWIC 2007Skypes slow adaptation to bandwidth drop causes coexisting TCP flows to be suppressed.Skypes over-utilization of bandwidth causes massive fluctuation on bitrate, which may result in user frustration.

Network and Systems, there are many to be improved on Skypes rate adaptation algorithm.Skypes over-utilization of bandwidth is1) wasting network resource and2) threating other applications at the risk of3) producing massive fluctuation on quality.Our major assumption: This selfish deed of Skype is actually NOT helping user satisfaction. Users dislike changes on audio quality, even if they actually increase the average rate.Network and Systems and Systems and Systems our assumption about users impression towards audio quality fluctuation.Get a ballpark idea of the possible relationships between parameter and MOS. (formulation)

Network and Systems audio encoder/decoder to create audio track with fluctuating qualities (bitrates.)We will focus on Silk in all following experiments due to its1) potential of domination of VoIP codec and2) flexibility on fine-tuning bitrate.

Network and Systems TracksHigh rateLow rateTimeTTBitrateNetwork and Systems





Test Tracks Setup


EncoderEncoderDecoderDecoderHigh rateLow rateCombineTHeader

Network and Systems GoalWe target three variables, High Rate, Low Rate, T, that affect the users perception.Interactions between the three variables.Exp1: Find the relation between fixed bitrate and MOS.

Exp2: Find the formula that combines the three dimensions with MOS.

Network and Systems Test Tracks SetupThe maximum and minimum bitrate of Silk are 40.6 and 5.6 kbps.We chose 10 rates uniformly from the interval.

Experiment 1: Fixed Rate vs. MOSq140.6 kbpsq236.6 kbpsq332.8 kbpsq428.9 kbpsq525.0 kbpsq621.1 kbpsq717.2 kbpsq813.3 kbpsq99.5 kbpsq105.6 kbpsNetwork and Systems Test Tracks SetupThe source track is 30 seconds long. We set T as its factors.We picked 4 rates (q1, q4, q7, q10) to be the candidates of high and low rates.

HRLRT10 sec5 sec3 sec2 sec1 sec{40.6, 28.9, 17.2, 5.6} kbpsExperiment 2Network and Systems Test Tracks SetupFollows the ITU recommendations.Four voices: 2 male and 2 female.Sentences with no coherent plot.30 seconds, 44.1 kbps

Reference tracks (original 44.1 kbps) are inserted in the test cases in order to provide a standard of rating.The tracks of Exp1&2 are mixed up and the order of rating for each subject is randomly picked.Network and Systems Results (Exp1)

Network and Systems Analysis (Exp1)The plot can be fitted by a shifted logarithm function.The shift is due to the lower boundary of human audio perception.Observed rapid MOS drop with lower bitrate.

Network and Systems Logarithms?WeberFechner lawThe smallest noticeable difference in stimulus (the least difference that the test person can still perceive as a difference,) was proportional to the starting value.

The law is shown plausible in a wide range of human perceptions including hearing, vision, taste, sense of touch and heat, and even temporal and spatial cognitions.

Network and Systems Results (Exp2)Adapting to an optimal rate and ignoring how users feel about changes might be over-optimistic.

Network and Systems Results (Exp2)

Network and Systems Analysis (Exp2)R2 of logarithm regression of each track are generally higher than 0.9.An outlier is discovered: 28.9+17.2. This is attributed to:1) the similarity of the two bitrates and 2) they both reside in middle- or low-level qualities. The phenomena is also supported by the ANOVA test on the similarity of 28.9 and 17.2 kbps data sets (p = 0.2155).Network and Systems Analysis (Exp2)In short, the MOS to frequency of rate change relationship, although shows logarithmic behavior in general, depends on the magnitude of rate changes. Network and Systems Guessing About the SubroutinesSCALE()Directly associated with the difference between hr and lr. The results in Fig. 7 provide evidence to this inference: same average bitrate, different magnitudes.Positive correlation between the scale of regression function and rate change magnitude. Another intention of SCALE() is to deal with small magnitude tracks that does not fit well.

Network and Systems Guessing About the SubroutinesSHIFT()Cope with humans expectation. As T grows, the effect of fluctuation decreases and the variable-rate case will become indiscernible to a fixed-rate version. We call this imaginary, fixed rate equivalent the dominant quality of the fluctuation. (dominant quality average quality)The dominant quality is the exact quality a user expects to observe when the negative impact of fluctuation diminishes. Network and Systems and Systems Experiments: GoalWe need massive data to construct the detail of our formulas:- verify the structures of our formulas.- factors in the fixed-rate formula:

- subroutines in the variable-rate formula: SCALE(hr,lr) & SHIFT(hr,lr)Network and Systems source track.Nine levels of quality are exponentially chosen.Five levels of rate changing frequency {1,2,3,5,10}.127 participants.Score calibration with hidden reference track.ITU RecommendationsNetwork and Systems Formula StructureFigural support:Non-parallel plotsStatistic support:ANOVA of interactivity (p=8e-14)

Network and Systems Fixed-rate Formula=4.091=1.515=1.000

Another interesting discovery: lower bound of Silk.

Network and Systems SCALENot surprisingly, SCALE subroutine is positively correlated with magnitude.

Network and Systems SHIFTThis is more tricky due its relationship with user expectation.Base on our definition of dominant quality:

Where D(hr,lr) is the MOS of the dominant quality of rate changing pair: (hr,lr)

Network and Systems (Conti.)First we plot the estimated MOS of fixed hr, fixed lr, and D.There is an apparent difference when hr

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