HRTF Database Matching Through Calibration Error Profiles
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Solution Overview
Problem
Existing systems struggle to provide personalized and immersive audio experiences for interactive content due to the unique physical interactions of each user's head, making it impractical to measure and replicate individual head-related transfer functions (HRTFs) for millions of users.
Innovation Solution
A method and system that generates a library of HRTFs for a plurality of reference individuals, allowing users to calibrate their audio experience by matching sound locations with their unique head shape, using a calibration test to identify the closest matching HRTF from the library without direct measurement, and optionally blending HRTFs for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual HRTF measurement is performed for each user, then audio personalization quality is improved, but device complexity and time consumption increase significantly
Solution Approach 1:
The patent creates a library of HRTF profiles from reference individuals and uses these copies to match with target users through calibration tests, avoiding the need for complex individual measurements while maintaining personalization quality
Solution Approach 2:
The patent introduces calibration tests as an intermediary mechanism that bridges the gap between reference HRTF profiles and target users, enabling indirect HRTF determination without direct measurement equipment
2Measurement precision
If individual HRTF measurement is performed for each user, then audio personalization quality is improved, but time consumption increases
Solution Approach 1:
The patent pre-generates a library of HRTF profiles from reference individuals before actual user matching, allowing rapid calibration through comparison rather than time-consuming individual measurements
Solution Approach 2:
By using pre-recorded HRTF profiles as templates, the system enables quick matching through calibration tests rather than performing lengthy individual measurements for each user
3Measurement precision
If a large HRTF library is created with many reference individuals, then matching accuracy is improved, but data storage requirements increase
Solution Approach 1:
The patent transforms complete HRTF measurements into condensed calibration profiles that capture essential characteristics, reducing storage requirements while preserving matching accuracy
Data Source
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AI summary
An audio personalisation method for a first user comprises testing a first user on a calibration test, the calibration test comprising requiring a user to match a test sound to a test location, either by controlling the position of the presented sound or controlling the position of the presented location, for a sequence of test matches, each test sound being presented at a position using a default head related transfer function 'HRTF', receiving an estimate of each matching location from the first user, and calculating a respective error for each estimate, to generate a sequence of location estimate errors for the first user; and comparing at least some of the location estimate errors for the first user with estimate errors of the same locations previously generated for at least a subset of a corpus of reference individuals; identifying a reference individual with the closest match of compared location estimation errors to those of the first user; and using an HRTF, previously obtained for the identified reference individual, for the first user.