Ambisonic Spatial Audio Quality Metrics
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Solution Overview
Problem
Current technologies lack objective quality metrics to measure the perceived quality and spatial localization accuracy of streamed spatial audio, particularly in ambisonic formats, which are essential for maintaining user experience in limited bandwidth networks.
Innovation Solution
The development of an objective audio quality metric, AMBIQUAL, which predicts users' quality of experience by estimating Listening Quality and Localization Accuracy of compressed ambisonic signals using spectro-temporal similarity measures derived from B-format ambisonic audio streams, eliminating the need for costly and time-consuming listening tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If compression techniques are applied to ambisonic signals for efficient streaming, then bandwidth usage is reduced and streaming efficiency is improved, but objective quality metrics and spatial localization accuracy measurement capabilities are lost
Solution Approach 1:
The patent applies preliminary action by pre-defining objective quality metrics (OQM) and spatial localization accuracy metrics before compression is applied. These metrics are established as reference standards that can be used to evaluate compressed signals without requiring actual listening tests, thus enabling quality assessment to be performed in advance and efficiently during streaming operations.
Solution Approach 2:
The patent introduces intermediary metrics as mediators between the compressed ambisonic signals and human perception. Instead of directly measuring perceived quality through listening tests, the patent uses objective quality metrics (OQM) and spatial localization accuracy metrics as intermediate measurements that correlate with human perception, enabling efficient automated quality assessment.
2Measurement precision
If listening tests are conducted to evaluate ambisonic signal quality, then accurate quality assessment is achieved, but time consumption and cost increase significantly
Solution Approach 1:
The patent applies copying by creating objective mathematical models (OQM and spatial localization accuracy metrics) that replicate the functionality of human listening tests. These metric models copy the essential assessment capabilities of subjective listening tests but execute automatically through algorithms, eliminating the need for actual human listeners while maintaining assessment accuracy.
Solution Approach 2:
The patent replaces the mechanical system of human listening tests with automated computational metrics. Instead of relying on human ears and brains to evaluate quality, the patent substitutes mechanical/computational algorithms (OQM and spatial localization metrics) that process signals mathematically to produce quality assessments, dramatically reducing time and cost.
3Reliability
If high bandwidth is allocated for spatial audio streaming, then audio quality and localization accuracy are maintained, but network resource consumption increases
Solution Approach 1:
The patent applies feedback by using objective quality metrics (OQM) and spatial localization accuracy metrics to monitor the quality of compressed ambisonic signals during streaming. These metrics provide feedback information about signal quality and localization accuracy, enabling dynamic adjustment of compression parameters and bandwidth allocation to maintain acceptable quality while optimizing network resource usage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
AMBIQUAL provides an efficient method to assess and improve encoding schemes for ambisonic signals, ensuring optimal quality and localization accuracy in spatial audio streaming, suitable for applications like VR/AR and streaming services.
Implementation Method 1
a computing device may generate spectrograms, for example, using short-time Fourier transform, for a plurality of channels of reference and test ambisonic signals
Data Source
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AI summary
A computing device includes a processor and a memory. The processor is configured to generate spectrograms, for example, using short-time Fourier transform, for a plurality of channels of reference and test ambisonic signals. In some implementations, the test ambisonic signal may be generated by decoding an encoded version of the reference ambisonic signal. The processor is further configured to compare, for each of the plurality of channels of a reference ambisonic signal, at least a patch associated with a channel of the reference ambisonic signal with at least a corresponding patch of a corresponding channel of the test ambisonic signal and determine a localization accuracy of the test ambisonic signal based on the comparison. In some implementations, the comparing may be based on phaseograms of the reference and test ambisonic signals.