1. Error-Tolerant Audio Coding Workshop
Networked Audio Track : Event N1
David Trainor, Director of Advanced Audio Research, CSR
26th October 2012
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2. Workshop Overview
 Some networked audio trends
– Hierarchical broadcast / multicast networks
• Wide-, local- and personal-area
– Real-time / interactive / low-delay audio services e.g. gaming
– Networks with more complex QoS characteristics (e.g. wireless)
• Convenient and inexpensive, but reliability is an issue
 Audio coding is vital (e.g. network bandwidth management)
– Minimally affected by network reliability fluctuations
 This workshop discusses
– Approaches to and capabilities of error-tolerant audio coding
– Recent advances in state-of-the-art
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3. Your Panellists
 Dr David Trainor, CSR (Workshop Chair)
 Dr Gary Spittle, Dolby Labs
 Dr Deepen Sinha, ATC Labs
 Dr Bernhard Grill, Fraunhofer IIS
 Workshop Format
– 25 minute presentation by each panellist
• (20 minutes + 5 minutes Q&A)
– 15-20 minute general Q&A session
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4. Error-Tolerant Audio Coding
General Concepts and Techniques
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5. Classification of Audio Error Control Strategies
 Error correction
– FEC versus ARQ
– Dependent source coding versus independent source coding
– Typically exhibits two levels of success
• Corrects each error event flawlessly or fails completely
 Error limiting
– Limiting of catastrophic propagation of error events
– Sender-based, Receiver-based or Sender-and-Receiver-based
– Dependent source coding versus independent source coding
– Several levels and measures of “success” in perceptual terms
• Error propagation can continue to different degrees, but not
beyond a prescribed limit
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6. Classification of Audio Error Control Strategies (2)
 Error concealment
– Reduce perceptual significance of error events
– Sender-based, Receiver-based or Sender-and-Receiver-based
– Dependent source coding versus independent source coding
– Many levels and measures of “success” in perceptual terms
• PEAQ/PESQ objective testing
• Subjective quality measurements
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7. Error Correction with Independent Source Coding
 Applied at networking baseband or media access layer
– CRC-based detection
– FEC codes
– ARQ retransmissions
 Redundancy not applied in an audio-optimized way
– Packet payload treated as arbitrary data (equal error protection)
 Bit-rate and delay compromises
– Packet-based networks may require additional time-domain
interleaving, etc
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8. Error Correction with Dependent Source Coding
 Coded syntax protection prioritization
– Each field protected according to perceptual significance
– Unequal error protection across coded frame/stream fields
 Scalable coding
– Each coded layer protected according to perceptual significance
– Unequal error protection across coded layers
 These techniques augmented by network QoS prioritization
– Send critical coded frame values or coded audio layers over
network channels with higher QoS parameters
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9. Unequal Error Protection Examples
NON-SCALABLE CODEC
Field
1
Field 2 Field 3 ... Field
N-1
Field N Coded Frame
SCALABLE CODEC
Field
1
Field
2
Field 3 ... Field
N-1
Field N
Mid-Quality Stereo
Base Layer
Field
1
Field 2 Field 3 ... Field N-1
Field High-Quality Stereo
N Enhancement Layer
Field
1
Field
2
Field 3 Field 4 ... Field N-1
Field Parametric Upmixing
N Enhancement Layer
Green = low protection
Orange = medium protection
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Red = high protection
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10. Error Correction with Dependent Source Coding (2)
 Joint quantization and error control code insertion
– Trade small quantization noise increase for improved robustness
 Dynamic data segmentation
– Encode time-varying amounts of audio data
– Choose audio block size based on (for example)
• Communications channel reliability (probability of data loss)
• Network baseband packet size
 Possible compromises of error correction + audio coding
– Bit-rate, delay, codec computational complexity
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11. Error Limiting with Dependent Source Coding
 Key goal is to provide frequent points of resynchronization
– Error event can’t propagate beyond the next synchronization point
 Special synchronization codes/values
– Zero or low probability of occurrence in actual coded audio values
 Error Resilient Entropy Coding
– Insert variable-length entropy codes into fixed-length “slots”
– Partial codes take up spare space at the end of future slots
– Each slot guaranteed to start with first bit of a valid entropy code
– Codes are self-delimiting, hence frequent synchronization points
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12. Error Resilient Entropy Coding Concept
Insert variable length
codes in fixed-length
slots
Slot 1 Slot 2 Slot 3 Slot 4 Slot 5 Slot 6 Slot 7 Slot 8
Partial codes that don’t
fit in their slot are put into
the spare space in later
slots
Start of a code.
Frequent point of synchronization
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13. Error Limiting with Dependent Source Coding (2)
 Reversible Variable Length Codes
– Code sequence readable both forward and backwards in time
– Parsing in both directions can reveal inconsistencies and hence
errors.
 Fixed-length coding techniques
 Limit differential coding techniques
– Restart the differential or progressive coding technique
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14. Error Concealment with Independent Source Coding
 Padding silence or wideband noise
 Pitch estimation and synthesis
– Estimate dominant pitches from previous good frames
– Smooth discontinuities at boundaries
 Replacement with previous best-matching segments
– Simpler forms may be correlation-based
– Sophisticated forms
• SoFi (University of Ulster). MPEG-7 + semantic song analysis.
 Filtered wideband noise generation
– Noise shaped using spectrum of previous good frames
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15. Error Concealment with Independent Source Coding
 Dynamic data segmentation (discussed previously)
 Coded domain interleaving
– Spectral (packet loss only affects specific frequencies)
– Linear Prediction quantized prediction errors
 Linear Predictive Coding specific methods
– Coder parameters
• Copy coder parameters from last good frame
• Coder parameters from last good frame with scaled-down gains
– Stimulate predictor with statistically-shaped synthesized data
(coded residuals)
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