Personalized HRTF Management Across Applications and Audio Equipment
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Solution Overview
Problem
Conventional technologies fail to flexibly utilize head-related transfer functions (HRTFs) across multiple applications and devices, leading to inconsistent and suboptimal audio experiences due to OS constraints and lack of equipment-specific adjustments.
Innovation Solution
An information processing apparatus that associates HRTFs with user identifiers and equipment identifiers, enabling dynamic delivery and application of personalized HRTFs tailored to the user's equipment through a cloud server and app framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a head-related transfer function is individually calculated for each user, then the feeling of localization of the sound image is enhanced, but the system cannot flexibly use the head-related transfer function across multiple applications and devices
Solution Approach 1:
The system separates the head-related transfer function data from the application context by storing it in a dedicated storage unit with unique identifiers. This segmentation allows the HRTF data to be independently managed and accessed by multiple applications without being tied to a single application's architecture.
Solution Approach 2:
The system introduces an intermediary management layer that includes storage units, identification units, and selection units. This intermediary layer mediates between the calculated HRTF and various applications, enabling flexible access and appropriate selection based on equipment identifiers while preserving the personalized localization accuracy.
2Reliability
If a head-related transfer function is calculated for each user, then realistic sensations are enhanced, but the system cannot adjust the head-related transfer function according to the situation or audio equipment used
Solution Approach 1:
The system implements dynamic adjustment capability by enabling the selection unit to choose different HRTF data based on equipment identifiers and situational context. The system can dynamically switch between different HRTF datasets to match the audio equipment being used, maintaining realistic sensations while adapting to various situations.
Solution Approach 2:
The system changes the parameter of HRTF selection based on equipment identifiers. By comparing the equipment identifier with stored identifiers, the system selects the appropriate HRTF dataset that matches the current audio equipment, thereby adjusting the acoustic parameters to suit the specific situation and device.
3Adaptability or versatility
If head-related transfer function data is stored with equipment identifiers, then the system can match HRTFs with user equipment, but the system complexity increases
Solution Approach 1:
The system performs preliminary action by pre-storing equipment identifiers alongside HRTF data in the storage unit. This advance preparation eliminates the need for complex real-time equipment characterization, as the matching process simply compares identifiers rather than analyzing equipment properties from scratch.
Solution Approach 2:
The system uses copying by storing equipment identifiers as simple data representations rather than maintaining complex equipment models. This copying approach allows the system to reference equipment characteristics through lightweight identifier data, reducing overall system complexity while maintaining the capability for equipment-specific HRTF matching.
Data Source
AI summary
An information processing apparatus according to the present disclosure includes an executing unit that associates a head-related transfer function corresponding to a user with an identifier that identifies equipment that is used by the user and a providing unit that provides the head-related transfer function and the identifier associated with the head-related transfer function to a providing destination to which the head-related transfer function corresponding to the user is provided.