Spatial Audio Parameter Encoding with Object-Based Bit Allocation
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Solution Overview
Problem
Existing spatial audio encoding methods fail to efficiently utilize synergies in processing spatial metadata derived from microphone arrays and audio objects, leading to inefficient bit allocation and compression when these metadata are processed separately.
Innovation Solution
A method and apparatus for bit-efficient encoding of spatial audio parameters, which determines a bit-efficient encoding for audio direction parameters by comparing directional differences between metadata from microphone arrays and audio objects, using spherical quantization and masking parameters to optimize bit allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If spatial metadata from microphone arrays and audio objects are processed separately, then processing simplicity is maintained, but compression efficiency and bit allocation optimization deteriorate
Solution Approach 1:
The patent merges the processing of spatial metadata from microphone arrays with audio object metadata by introducing a masking mechanism. The encoder compares spatial parameters (azimuth, elevation) of microphone array metadata against audio object metadata to determine masking relationships. When metadata is masked by an audio object, it can be encoded more efficiently by referencing the audio object's spatial parameters rather than encoding full precision values, thereby improving compression efficiency while maintaining a manageable processing complexity through systematic comparison and masking rules.
2Measurement precision
If directional parameters are encoded with high precision, then spatial audio quality is improved, but bit rate increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the precision of directional parameter encoding based on masking relationships. When spatial metadata is masked by an audio object, the encoder reduces the precision requirements for encoding azimuth and elevation parameters, using differential encoding or referencing the audio object's spatial parameters. This allows high spatial audio quality to be maintained for unmasked metadata while significantly reducing bit rate for masked metadata, achieving an optimal balance between precision and bit rate through adaptive parameter adjustment.
Data Source
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AI summary
A method comprising: obtaining a first audio direction parameter value for each sub-band of a sub-frame of a frame of an audio signal; obtaining a second audio direction parameter value for the sub-frame of the frame of the audio signal for one or more audio objects associated with said audio signal; and determining a bit-efficient encoding for each first audio direction parameter value of the sub-frame based on a similarity between the first audio direction parameter value for each sub-band and the second audio direction parameter values for the one or more audio objects.