HOA Signal Compression via Subband Directional Prediction
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Solution Overview
Problem
Higher Order Ambisonics (HOA) representations require high bit rates for transmission, making existing compression methods inadequate for applications like audio streaming to mobile devices, which demand lower data rates without compromising sound quality.
Innovation Solution
A method for low-bit rate compression of HOA representations by decomposing the signal into frequency subbands, approximating coefficients with a truncated HOA representation and predicted directional subband signals, and encoding these components efficiently to reduce data requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HOA representation is transmitted with high sampling rate and bit depth, then sound quality is improved, but data rate becomes too high for practical applications
Solution Approach 1:
The HOA signal is divided into multiple frequency subbands using filter banks. Each subband is processed independently with subband-specific directional signals and prediction parameters, allowing efficient compression while preserving audio quality across different frequency ranges.
Solution Approach 2:
The number of directional signals and their directions are adapted dynamically for each subband based on the local spectral characteristics. This allows the encoding to concentrate resources where needed (directional components) and use simpler representation where ambient sound dominates, optimizing the trade-off between quality and bit rate.
2Quantity of substance
If existing compression methods are used, then some compression is achieved, but data rate remains too high for mobile streaming applications
Solution Approach 1:
The encoder uses prediction mechanisms where past directional signals and HOA coefficients are used to predict current values. The prediction errors are then encoded, significantly reducing the amount of data that needs to be transmitted while maintaining reconstruction accuracy.
Solution Approach 2:
The method transforms the HOA representation from a fixed coefficient set into a dynamic representation with subband-specific directional signals, prediction parameters, and adaptive selection of active coefficients. This parameter transformation enables much more efficient compression suitable for mobile streaming.
Data Source
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AI summary
Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates. A method for low bit-rate encoding frames of an input HOA signal having coefficient sequences comprises computing (s110) a truncated HOA representation (C T (k)), determining (s111) active coefficient sequences (lc,Act(k)), estimating (s16) candidate directions (MDIR(k)), dividing (s15) the input HOA signal into a plurality of frequency subbands (f 1,..., f F), estimating (s161) for each of the frequency subbands a subset of candidate directions (MDIR(k)) as active directions (MDIR(k,f1),..., MDIR(k,fF)) and for each active direction a trajectory, computing (s17) for each frequency subband directional subband signals from the coefficient sequences of the frequency subband according to the active directions, calculating (s18) for each frequency subband a prediction matrix (A(k,f1),...,A(k,fF)) that can be used for predicting the directional subband signals from the coefficient sequences of the frequency subband using the respective active coefficient sequences (Ic,ACT(k)), and encoding (s19) the candidate directions, active directions, prediction matrices and truncated HOA representation.