Immersive Audio Bitstream Encoding for Low-Latency Wireless Playback
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Solution Overview
Problem
Existing audio streaming technologies face challenges in achieving low latency and efficient transmission of immersive audio programs over wireless links, especially when combined with other types of information, due to varying wireless quality and complex user setups.
Innovation Solution
A method for encoding and decoding immersive audio programs involves segmenting audio signals into overlapping frames, transforming them into frequency-domain signals, quantizing and coding these signals, and assembling them into independent blocks for low latency transmission and playback, with support for flexible rendering and echo-management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If audio signals are transmitted over wireless links with complex user setups, then audio distribution reaches multiple devices, but latency increases and transmission quality deteriorates
Solution Approach 1:
The audio signal is divided into multiple independent blocks, each containing a frame of audio data. This segmentation allows selective transmission and processing of individual blocks, reducing overall latency while maintaining flexible distribution across multiple devices. Each block can be processed and transmitted independently, enabling parallel processing and reducing the critical path delay.
Solution Approach 2:
The audio signal undergoes pre-processing including frame extraction, MDCT transformation, and quantization before transmission. This preliminary action prepares the signal in an optimized format that reduces processing latency at the receiving end and enables efficient error resilience mechanisms to be applied in advance.
2Productivity
If perceptually motivated quantization is applied to frequency-domain signals, then coding efficiency improves, but quantization error increases
Solution Approach 1:
Perceptually motivated quantization is applied selectively to different frequency bands based on human auditory perception characteristics. Critical frequency regions receive finer quantization to preserve important audio information, while less critical regions use coarser quantization to achieve better compression. This local quality approach optimizes the trade-off between coding efficiency and perceived audio quality.
Solution Approach 2:
The quantization error, which would normally be harmful, is converted into a benefit through error resilience mechanisms. The encoded audio blocks include error detection and correction capabilities that transform quantization artifacts into manageable noise floor, actually improving robustness against transmission errors and enhancing overall error resilience.
3Reliability
If audio frames are segmented into overlapping frames, then error resilience improves, but processing complexity increases
Solution Approach 1:
The audio signal is segmented into overlapping frames where each frame shares portions with adjacent frames. This segmentation provides error resilience because if one frame is corrupted during transmission, the overlapping portions from adjacent frames can be used for error correction and reconstruction. The independent block structure allows this overlap to be implemented efficiently without requiring complex inter-frame dependencies.
Solution Approach 2:
The overlapping frame structure implements partial redundancy by transmitting more audio data than strictly necessary for perfect reconstruction. This excessive action in terms of data transmission provides error resilience margins, allowing the system to tolerate transmission errors while maintaining acceptable audio quality. The redundancy is partial rather than complete, balancing error resilience with transmission efficiency.
Data Source
AI summary
A method for encoding audio signals of an immersive audio program for low latency transmission to one or more playback devices, the method comprising: receiving a plurality of time-domain audio signals of the immersive audio program; extracting a frame of the time-domain audio signals, wherein the extracted frame of the time-domain audio signals overlaps with a previously extracted frame of time-domain audio signals, thereby segmenting the audio signals into overlapping frames; transforming the frame of time-domain audio signals to frequency-domain signals; quantizing the frequency-domain signals using a perceptually motivated quantization tool; coding the quantized frequency-domain signals; assembling the quantized and coded frequency-domain signals into one or more independent blocks within the frame; and assembling the one or more independent blocks into an encoded frame.


