Space sound scene self-adaptive control method with head tracking function

By performing time alignment and filtering on head posture data, a head state sequence is constructed and multi-scale decomposition is performed to generate a perceptual factor vector, construct a spatially perceptual stable potential field, and adjust the sound source parameters. This solves the problem of unstable sound image localization in head tracking spatial audio control methods under complex motion scenarios, and improves sound image stability, response balance, and adaptive capability.

CN122093735AActive Publication Date: 2026-05-26SHENZHEN XINGMAN SMART TECH CO LTD
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Patent Information

Application Number
CN202610564464.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-27
Publication Date
2026-05-26
Estimated Expiration
2046-04-27

AI Technical Summary

Technical Problem

Existing head-tracking spatial audio control methods struggle to distinguish between conscious rotation and unconscious jitter in complex motion scenarios, leading to unstable sound image localization. Furthermore, a single control parameter cannot simultaneously address both response speed and positioning accuracy.

Method used

By acquiring head posture data, performing time alignment and filtering, a head state sequence is constructed, and multi-scale decomposition is performed to generate spatial perturbation factors, motion trend factors, and gaze lock factors. A spatially perceptual stable potential field is constructed, and sound source parameters are adjusted to generate a set of target soundscape parameters.

Benefits of technology

It improves the stability and response balance of the audio-visual system, enhances the system's adaptability, reduces computational complexity, and is suitable for real-time implementation.

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Abstract

The invention discloses a space voice scene self-adaptive control method with a head tracking function, and relates to the technical field of space audio processing and man-machine interaction, and the method comprises the steps: obtaining head posture data, and executing time alignment and filtering processing to obtain a head state sequence; based on the head state sequence, performing multi-scale decomposition processing in a preset time window to obtain a multi-scale behavior feature set; on the basis of the multi-scale behavior feature set, constructing a perception factor vector representing a head motion state; constructing a spatial perception stable potential field based on the perception factor vector and the current head posture; and in a sound image change tolerance range limited by the spatial perception stable potential field, carrying out constraint adjustment on sound source parameters in the spatial sound scene, and generating a target sound scene parameter set. Dynamic self-adaptive control is achieved by distinguishing conscious rotation and unconscious jitter, sound image stability and response sensitivity are both considered, immersion experience is enhanced, and calculation is efficient.
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