Microphone Modeling via Spatial Impulse Response Matching
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Solution Overview
Problem
Existing microphones lack the ability to adapt and imitate the characteristics of other microphones effectively, limiting their versatility in capturing and reproducing specific audio patterns and polar responses.
Innovation Solution
A method and device for modeling microphone characteristics involve measuring the impulse response of target microphones over different angles, performing signal conditioning, and using spatial response matching algorithms to determine filter and model parameters, allowing the microphone to mimic the target microphone's behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a microphone uses fixed filter parameters, then the device structure is simple, but the adaptability to different microphone characteristics is poor
Solution Approach 1:
The patent applies preliminary action by pre-determining filter parameters through spatial impulse response measurements of target microphones. The filter parameters are calculated in advance based on measured spatial characteristics, allowing the microphone to adapt to different microphone types without requiring complex real-time adjustment mechanisms. This resolves the contradiction by preparing the adaptation data beforehand, simplifying the actual device operation while maintaining high adaptability.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting filter parameters based on the selected target microphone characteristics. Different filter parameters are stored and applied depending on which microphone type is being emulated, allowing the same physical microphone to change its acoustic characteristics. This enables high adaptability without requiring multiple physical microphones, resolving the contradiction between versatility and device complexity.
2Measurement precision
If spatial impulse response measurements are performed for accurate modeling, then the adaptability improves, but the measurement and processing time increases
Solution Approach 1:
The patent applies preliminary action by performing spatial impulse response measurements and filter parameter calculations in advance, before actual use. The comprehensive spatial measurements are conducted during a setup phase, and the results are stored as reusable filter parameters. This resolves the contradiction by shifting the time-consuming measurements to a preliminary stage, allowing fast operation during actual microphone emulation without sacrificing measurement precision.
Solution Approach 2:
The patent implements dynamics by creating a dynamic relationship between spatial measurements and filter parameters. The system adaptively selects and applies appropriate filter parameters based on the desired microphone characteristics, allowing the same measurement data to serve multiple emulation purposes. This enables accurate modeling across different microphone types without repeating measurements, reducing time loss while maintaining precision.
3Adaptability or versatility
If multiple filter parameters are stored for different microphone types, then the versatility improves, but the memory requirements and data management complexity increases
Solution Approach 1:
The patent applies universality by designing a single microphone device that can emulate multiple different microphone characteristics through programmable filter parameters. Instead of requiring multiple physical microphones or extensive separate data sets, the system uses a universal framework where filter parameters are adjusted to achieve different acoustic responses. This reduces the quantity of data needed while maintaining high versatility, as the same hardware and processing framework serves multiple emulation purposes.
Data Source
AI summary
A method of modelling microphone characteristics of a target microphone is provided. An impulse response of target microphones is measured over different angles. A signal conditioning on the measurement data is performed. The spatial response based on a spatial response matching algorithm is matched and filter parameters and/or model parameters are determined.