Personalized Audio Response Modeling from Image-Derived Acoustic Features
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Solution Overview
Problem
Current solutions for customizing audio experience for individuals are inadequate as they rely on matching a subject's image with a BRIR/BRTF database, which is not ideal.
Innovation Solution
A processing method and apparatus that captures an individual's image, processes it to generate input signals, and combines them with database signals to produce customized audio response characteristics, applying them to input audio signals for personalized audio experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image matching with BRIR/BRTF database is used to customize audio experience, then audio personalization is achieved, but matching accuracy and customization quality deteriorate
Solution Approach 1:
The patent introduces intermediate features (spectral features, temporal features, statistical features) as mediators between the input image and the BRIR/BRTF database. These intermediate features serve as a bridge that transforms visual information into acoustic characteristics more accurately than direct image matching, resolving the contradiction by improving matching accuracy through multi-stage feature transformation.
Solution Approach 2:
The patent replaces the mechanical image-matching system with a neural network-based acoustic feature generation system. Instead of directly matching images to database entries, the system uses deep learning models to synthesize personalized BRIR/BRTF characteristics from image inputs, achieving superior customization quality through intelligent algorithms rather than brute-force matching.
2Productivity
If simple image matching is used, then processing speed is maintained, but audio customization quality deteriorates
Solution Approach 1:
The patent performs preliminary extraction of multiple types of features (spectral, temporal, statistical) from the input image before the main matching process. This preliminary action prepares the data in advance, enabling faster and more accurate processing in subsequent stages, thus maintaining processing speed while improving customization quality through comprehensive feature analysis.
Solution Approach 2:
The patent segments the audio customization process into multiple independent stages: feature extraction, intermediate feature generation, database matching, and parameter synthesis. This segmentation allows each stage to be optimized independently, maintaining overall processing speed while improving customization quality through specialized processing at each stage.
Data Source
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AI summary
The present disclosure relates to a system and a processing method in association with the system for customizing audio experience. Customization of audio experience can be based on derivation of at least one customized audio response characteristic which can be applied to an audio device used by a person. The customized audio response characteristic(s) can be unique to the person.