Room-Dependent Timbre Control Using Adaptive RIR Estimation
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Solution Overview
Problem
Existing acoustic control systems face challenges in accurately estimating the room impulse response (RIR) in environments with external influences like background noise, leading to signal-to-noise ratio deterioration and suboptimal adaptation processes.
Innovation Solution
A system comprising a loudspeaker, microphone, and a room-dependent gain-shaping block that uses the delayed coefficients method to estimate the RIR, employing a least mean square algorithm and psychoacoustic frequency scales to adjust gain based on reference and estimated room data, ensuring robust adaptation and reduced memory consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional acoustic control systems estimate RIR in environments with background noise, then the system can operate in real-world conditions, but the signal-to-noise ratio deteriorates and measurement precision decreases
Solution Approach 1:
The patent converts the harmful background noise into a beneficial estimation source by using the noisy microphone signal to update the RIR model. The LMS algorithm processes the total signal (direct sound + reflections + noise) to adaptively estimate the RIR, transforming the noise from a detrimental factor into part of the adaptation process that maintains system operation in real-world conditions.
Solution Approach 2:
The system implements feedback by continuously using the microphone's total signal to update the RIR estimation through the LMS algorithm. This closed-loop approach allows the system to adapt to changing acoustic conditions and maintain accurate timbre control despite the presence of background noise, resolving the contradiction between operational versatility and measurement precision.
2Measurement precision
If the system processes detailed frequency data to maintain signal quality, then timbre control accuracy improves, but memory consumption increases
Solution Approach 1:
The patent transforms the detailed frequency domain data into a compact set of tonal parameters (pitch, loudness, timbre characteristics) that capture the essential acoustic information. This parameter transformation maintains timbre control accuracy while significantly reducing the memory resources required to store and process the acoustic data.
Solution Approach 2:
The system extracts only the critical tonal parameters from the full frequency spectrum data, separating the essential timbre information from the redundant details. This extraction approach allows accurate timbre control to be achieved with minimal memory consumption by focusing only on the most relevant acoustic characteristics.
3Stability of the object's composition
If the system continuously adapts to changing room acoustics, then timbre stability improves, but the adaptation process becomes more complex and computationally intensive
Solution Approach 1:
The system employs self-service through the LMS algorithm, which automatically adapts the RIR estimation using the available microphone signal without requiring external intervention or complex control logic. The algorithm self-regulates the adaptation process, adjusting to changing room acoustics while maintaining computational efficiency and system simplicity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively adapts to changing acoustic conditions, maintaining signal quality and reducing noise interference, while minimizing memory usage through psychoacoustic frequency scaling and interpolation of tonal changes.
Implementation Method 1
a loudspeaker configured to generate an acoustic sound output from an electrical sound signal
Implementation Method 2
a microphone configured to generate a total electrical sound signal representative of the total acoustic sound in the room
Data Source
AI summary
A system and method for automatically controlling the timbre of a sound signal in a listening room are also disclosed, which include the following: generating an acoustic sound output from an electrical sound signal; measuring the total acoustic sound level in the room and generating an electrical total sound signal representative of the total acoustic sound level in the room, wherein the total acoustic sound comprises the acoustic sound output generated from the electrical sound signal; and adjusting the gain of the electrical sound signal dependent on a room-dependent gain signal, the room-dependent gain signal being determined from reference room data and estimated room data.


