3D Audio Localization via Sensor-Based HRTF Customization
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Solution Overview
Problem
Existing 3D audio technologies face challenges in providing accurate, user-friendly, and cost-effective solutions for creating immersive audio experiences that accurately localize sound in 3D space, particularly due to variations in human anatomy and environment, which current head-related transfer functions (HRTFs) fail to adequately address.
Innovation Solution
The use of sensors to collect data on the listener's physical characteristics and environment, determining a suitable HRTF for each user, and generating a 3D audio signal based on this data to create a realistic sound localization experience compatible with existing audio systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a generic HRTF is used for all users, then the system is simple and cost-effective, but the sound localization accuracy deteriorates due to individual anatomical variations
Solution Approach 1:
The system performs preliminary scanning of the user's head and ear anatomy using depth sensors before audio playback. This preliminary action captures geometric data that is then used to generate a customized HRTF, eliminating the need for manual measurement or complex fitting procedures during actual use.
Solution Approach 2:
The system automatically generates and applies a customized HRTF based on sensor data without requiring user intervention for manual adjustment. The automated pipeline processes anatomical data, selects or generates appropriate HRTF parameters, and applies them to the audio signal, making the complexity invisible to the user.
2Measurement precision
If detailed sensor data collection is implemented to capture individual anatomy, then HRTF accuracy improves, but the cost and device complexity increase
Solution Approach 1:
The system extracts only the essential geometric features needed for HRTF calculation (head width, ear position, pinna shape) from the sensor data, rather than processing complete 3D scans. This extraction approach maintains accuracy while reducing computational burden and hardware requirements.
Solution Approach 2:
The depth sensing capability, originally designed for spatial mapping in augmented reality, is repurposed to capture anatomical features for HRTF generation. This multi-functionality allows the same sensor to serve both AR navigation and audio localization purposes, reducing overall system cost.
3Measurement precision
If real-time 3D audio processing is performed with customized HRTF, then sound localization accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system pre-calculates and stores HRTF parameters based on captured anatomical data before audio playback begins. This preliminary processing creates a customized audio filter that can be applied in real-time without extensive computation during actual sound reproduction.
Solution Approach 2:
The system dynamically adjusts HRTF parameters based on the user's head orientation and movement detected by sensors, maintaining accurate localization without requiring full reprocessing. Only the rotation and position parameters are updated in real-time, while the core anatomical-based HRTF remains static.
Data Source
AI summary
Techniques are provided for providing 3D audio, which may be used in augmented reality. A 3D audio signal may be generated based on sensor data collected from the actual room in which the listener is located and the actual position of the listener in the room. The 3D audio signal may include a number of components that are determined based on the collected sensor data and the listener's location. For example, a number of (virtual) sound paths between a virtual sound source and the listener may be determined. The sensor data may be used to estimate materials in the room, such that the affect that those materials would have on sound as it travels along the paths can be determined. In some embodiments, sensor data may be used to collect physical characteristics of the listener such that a suitable HRTF may be determined from a library of HRTFs.