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Modeling the effects of Burst Packet Loss and Recency on Subjective Voice Quality

Modeling the effects of Burst Packet Loss and Recency on Subjective Voice Quality. Alan Clark Telchemy alan@telchemy.com. Embedded Monitoring. Need to monitor QoS to provide feedback on network performance / impact on subjective quality

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Modeling the effects of Burst Packet Loss and Recency on Subjective Voice Quality

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  1. Modeling the effects of Burst Packet Loss and Recency on Subjective Voice Quality Alan Clark Telchemy alan@telchemy.com Telchemy – IPtel 2001

  2. Embedded Monitoring • Need to monitor QoS to provide feedback on network performance / impact on subjective quality • Desirable to provide monitoring in the form of a lightweight software agent • Focus on time varying impairments – burst packet loss and “recency” Telchemy – IPtel 2001

  3. Embedded Monitoring Gateway Gateway IP Network QoS metrics VQmon Agent embedded into VoIP Gateway SMS/NMS Telchemy – IPtel 2001

  4. The E Model • “Mouth to ear” transmission quality measurement • Produces an “R” factor typically in the range 50 (bad) -95 (good) • R factor can be related to MOS score, Terminate Early (TME) etc. • ITU G.107/ G.108 and ETSI ETR250 Telchemy – IPtel 2001

  5. R Factor vs MOS R Factor MOS 4.5 4.0 3.0 Telchemy – IPtel 2001

  6. E Model R = Ro - Is - Id - Ie + A Base R value - Noise level Advantage factor Equipment Impairment Factor - CODEC - multiplexing effects Impairments that occur simultaneously with speech - received speech level - sidetone level - quantization noise Impairments that are delayed with respect to speech - talker echo - listener echo - round trip delay Telchemy – IPtel 2001

  7. Extended E Model Packet Loss Loss Model Network R Factor Ie Burst model Jitter Model Jitter User R Factor Codec type Codec Model Recency model Delay model Delay, measured using RTCP Telchemy – IPtel 2001

  8. Burst of packet loss Zero packet loss Burst vs average loss Non-bursty packet loss Telchemy – IPtel 2001

  9. Instantaneous Quality Source France Telecom Telchemy – IPtel 2001

  10. “Recency” effect 60 second call MOS 3.82 MOS 3.28 MOS 3.18 “Bad” 1.8 MOS (3dB SNR) “Good” 4.3MOS Source AT&T T1A1.7/98-031 Telchemy – IPtel 2001

  11. Jitter and Packet Loss Monitor jitter and packet loss after jitter buffer Jitter buffer Arriving RTP packets CODEC Late packets discarded Telchemy – IPtel 2001

  12. Loss Model - Markov model Model parameters reconstructed at end of call 3 Lost P32 P23 2 Rcvd Burst state P31 P13 P22 1 Rcvd Gap state 4 Lost P14 P41 P11 Telchemy – IPtel 2001

  13. Loss Model - mapping loss to Ie Curve is CODEC dependant Telchemy – IPtel 2001

  14. Determining QoS metrics 1. Determine “good” and “bad” state Ie Factor Telchemy – IPtel 2001

  15. Determining QoS metrics t = 15 t = 5 1. Determine “good” and “bad” state Ie Factor 2. Estimate Instantaneous R Factor for each state Telchemy – IPtel 2001

  16. Determining QoS metrics t = 15 t = 5 3. Determine average Ie 1. Determine “good” and “bad” state Ie Factor 2. Estimate Instantaneous R Factor for each state Telchemy – IPtel 2001

  17. Delay effects 4 3 Mean Opinion Score Conversation 2 Verify sequence of random numbers 0 1 2 3 4 Delay (seconds) Source NTT Telchemy – IPtel 2001

  18. Measuring Delay Accumulate frame Encode Jitter buffer Transmission Decode CODEC CODEC RTCP exchange Telchemy – IPtel 2001

  19. Delay Model 175 mS “knee” R Factor Reduction End to end delay (mS) Telchemy – IPtel 2001

  20. Estimation of recency effect Effects decay over 30-60 seconds Average for call Delay since last significant burst Telchemy – IPtel 2001

  21. Execution model Call 1 Call 2 Start call End call Initialize Ports End call Start call Loss events Loss events Typically 1.4 assembly language instructions per packet Telchemy – IPtel 2001

  22. Integration with VoIP SMS Service Mgt System CDR End of call msg (DRQ) VQmon SNMP Set, Get, Trap Network Mgt System Telchemy – IPtel 2001

  23. Ranking accuracy – Set 1 Telchemy – IPtel 2001

  24. Ranking Accuracy – Set 2 Telchemy – IPtel 2001

  25. Ranking Accuracy – Set 4 Telchemy – IPtel 2001

  26. Conclusions • Computational model meets design goals • Ranking accuracy is comparable to human listener • But need - • Systematic comparison with PSQM/ PESQ • Increased level of subjective testing • Add support for VAD, non-PLC • Improved accuracy requires some information on voice frame content Telchemy – IPtel 2001

  27. Further work areas • Use CODEC generated frame loss event – indicate presence of speech energy • Additional subjective testing • Wider variety of audio sources • Force listeners to focus on call content • Design impairments to isolate recency effect, burst characteristics, masking effects Telchemy – IPtel 2001

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