Audio Quantization Parity Control for Bit Error Resilience
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Solution Overview
Problem
Existing audio data compression and decompression techniques face challenges in reducing bit errors and latency, especially in live audio transmissions, and often fail to interoperate with existing devices due to new compression schemes.
Innovation Solution
The proposed solution involves a stream-conformant bit error resilience technique that uses a specialized rounding operation to force a group parity value in audio data compression, allowing for error detection and correction while maintaining compatibility with existing standards through the use of arithmetic encoding and decoding, and incorporating parity residual values for enhanced error handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If re-transmission of encoded output is used to combat bit errors, then reliability is improved, but latency increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and embedding parity values during the encoding process. Instead of waiting for errors to occur and then re-transmitting data, the system proactively prepares error correction information in advance. The specialized rounding operation forces quantized values to satisfy parity constraints before transmission, enabling the receiver to detect and correct errors without requiring re-transmission, thus maintaining low latency while improving reliability.
2Reliability
If a new compression scheme is adopted to improve bit error resilience, then reliability is improved, but interoperability deteriorates
Solution Approach 1:
The patent applies parameter changes by modifying the quantization process parameters rather than changing the overall compression scheme. The specialized rounding operation adjusts how spectral values are quantized by forcing them to satisfy parity constraints, but the underlying MDCT transform and general compression structure remain unchanged. This allows existing decoders to still process the data while gaining improved error resilience, maintaining interoperability without sacrificing reliability enhancement.
3Reliability
If specialized rounding operation is applied to force parity values, then bit error detection capability is improved, but computational complexity increases
Solution Approach 1:
The patent applies self-service by having the quantization process itself generate the error detection capability. The specialized rounding operation forces quantized values to satisfy parity constraints, and the same process inherently creates the check mechanism. The system serves its own error detection needs through the rounding operation without requiring separate, complex error correction codes or additional processing stages, thus improving error detection while limiting the increase in computational complexity.
Data Source
AI summary
Methods, devices, non-transitory computer-readable medium, and systems are described for compressing audio data. The techniques involve obtaining a sequence of digitized samples of an audio signal, performing a transform using the sequence of digitized samples, to generate a plurality of spectral lines, obtaining a group of spectral lines from the plurality of spectral lines, and quantizing the group of spectral lines to generate a group of quantized values. Quantizing the group of spectral lines to generate the group of quantized values may comprise performing a specialized rounding operation on a spectral line selected from the group of spectral lines and using the specialized rounding operation to force a group parity value, computed for the group of quantized values, to a predetermined parity value. One or more data frames based on the group of quantized values may be outputted.