Spatial Positioning Vectors for Audio Encoding Adaptability
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Solution Overview
Problem
Current audio encoding technologies face challenges in encoding audio data to enable playback with arbitrary speaker configurations while maintaining backward compatibility with decoders that do not support Higher-Order Ambisonics (HOA) coefficients, as converting all audio data into HOA coefficients can result in larger bitstreams and compatibility issues.
Innovation Solution
An audio encoder determines and encodes spatial positioning vectors (SPVs) alongside the original audio data, allowing decoders to convert the audio into HOA coefficients for playback with arbitrary speaker configurations while ensuring backward compatibility by including the SPVs in the bitstream.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If all audio data is converted into HOA coefficients to enable playback with arbitrary speaker configurations, then adaptability to different speaker configurations is improved, but bitstream size increases and compatibility with older decoders deteriorates
Solution Approach 1:
The audio data is segmented into two parts: spatial positioning vectors (SPVs) that contain directional information, and audio coefficients that contain the actual audio content. This segmentation allows the decoder to reconstruct HOA coefficients only when needed, rather than transmitting all HOA coefficients in the bitstream, thus reducing bitstream size while maintaining adaptability.
Solution Approach 2:
The essential spatial information (SPVs) is extracted from the full HOA coefficient representation and transmitted separately. This extraction allows the bitstream to be smaller while still enabling arbitrary speaker configuration playback by combining the extracted SPVs with the audio coefficients at the decoder side.
2Adaptability or versatility
If all audio data is converted into HOA coefficients to enable arbitrary speaker configuration playback, then adaptability to different speaker configurations is improved, but compatibility with decoders that do not support HOA coefficients deteriorates
Solution Approach 1:
The bitstream is designed to be universal by including both SPVs and audio coefficients that can be interpreted in multiple ways. Modern decoders can use the SPVs and coefficients to generate HOA coefficients for arbitrary speaker configurations, while older decoders can interpret the same bitstream data in traditional multi-channel formats, ensuring backward compatibility.
Solution Approach 2:
The SPVs act as an intermediary that bridges between traditional audio formats and HOA formats. By including SPVs alongside audio coefficients, the system enables a transition path that allows both old and new decoders to process the same bitstream appropriately, with the SPVs serving as the mediating element that enables HOA functionality without forcing adoption.
3Productivity
If spatial positioning vectors are encoded alongside original audio data, then decoding efficiency is improved, but encoder complexity increases
Solution Approach 1:
The encoder transforms the audio representation by changing parameters from full HOA coefficients to a more compact form using SPVs and audio coefficients. This parameter change reduces the amount of data that needs to be processed during decoding, improving decoding efficiency while the encoder handles the transformation complexity only once during encoding.
Data Source
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AI summary
A device for processing audio data obtains data representing quantized versions of a set of one or more spatial vectors. Each respective spatial vector of the set of spatial vectors corresponds to a respective audio signal of the set of audio signals. Each of the spatial vectors is in a Higher-Order Ambisonics (HOA) domain and is computed based on a set of loudspeaker locations. The device inverse quantizes the quantized versions of the spatial vectors.