Personalized Audio Profiling Using In-Ear Sensors and Transfer Functions
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Solution Overview
Problem
Current methods for generating personalized audio profiles for listeners are expensive and not feasible with typical user computing devices, and existing approaches using anechoic chambers or neural networks are costly and inaccurate.
Innovation Solution
Generate personalized audio profiles using a computing device, such as a mobile device, by broadcasting sound and recording audio and position data with in-ear microphones and sensors, determining impulse responses, and applying filters to create a personalized transfer function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If measurements are made in an anechoic chamber using audio equipment, then the audio profile accuracy is improved, but the cost and complexity increase significantly
Solution Approach 1:
The patent uses a transfer function to mathematically model and copy the acoustic characteristics of an anechoic chamber environment. Instead of requiring physical anechoic chamber measurements, the system applies a transfer function that replicates the desired acoustic response, allowing standard devices to achieve professional-grade audio profiling without complex measurement equipment
Solution Approach 2:
The patent replaces the mechanical/acoustic measurement system (anechoic chamber, specialized audio equipment) with a computational approach using transfer functions and signal processing. The physical measurement infrastructure is substituted with mathematical models that compute the desired acoustic response directly from standard device recordings
2Measurement precision
If measurements are made in an anechoic chamber using audio equipment, then the audio profile accuracy is improved, but the cost increases significantly
Solution Approach 1:
The patent enables the use of inexpensive, readily available computing devices (smartphones, tablets, standard computers) to perform audio measurements that previously required expensive specialized equipment. The system transforms costly measurement infrastructure into affordable software-based solutions using standard consumer electronics
Solution Approach 2:
The patent replaces expensive physical measurement infrastructure with computational methods. Transfer functions and signal processing algorithms substitute for costly anechoic chamber facilities and professional audio equipment, dramatically reducing implementation costs while maintaining measurement accuracy
3Extent of automation
If neural networks are used to generate personalized audio profiles, then automation is improved, but accuracy deteriorates
Solution Approach 1:
The patent employs an iterative feedback process where the system records audio from multiple positions around the listener's head, analyzes the responses, and refines the transfer function through successive measurements. This feedback-driven approach achieves high accuracy by continuously optimizing the audio profile based on actual measured responses rather than relying on approximate neural network predictions
Data Source
AI summary
Disclosed implementations for determining a personalized audio profile. An audio signal and sensor data captured while a sound is broadcast from an audio source is received. Position data for the audio signal is determined based on the sensor data. A personalized audio profile is determined based at least on the audio signal and the position data. An audio stream is generated based on the second response.