Musical Instrument Pickup Signal Processor Feedback Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Acoustic instruments face challenges with sound reinforcement due to acoustic feedback and the limitations of traditional microphone systems, which can be expensive and prone to feedback, and acoustic pickups that often produce unsatisfactory sound quality.
Innovation Solution
A processing algorithm is developed to enhance the quality of acoustic instrument pickup signals by training on external microphone signals, allowing for the recreation of high-quality microphone signals without the need for microphones, using a combination of sensors and digital signal processing techniques to reduce feedback and improve sound fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If microphones are used for sound reinforcement, then sound quality is improved, but cost increases and acoustic feedback susceptibility worsens
Solution Approach 1:
The patent introduces a signal processing system as an intermediary between the pickup and amplification system. This intermediary processes the pickup signal to emulate microphone quality while maintaining the feedback-resistant properties of pickup-based systems, thus resolving the contradiction between sound quality and feedback susceptibility.
Solution Approach 2:
The patent creates a copy of microphone-quality sound output through digital signal processing. By analyzing pickup signals and synthesizing output that replicates microphone characteristics, the system achieves microphone-like sound quality without using actual microphones, thereby avoiding feedback issues.
2Measurement precision
If microphones are used for sound reinforcement, then sound quality is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical/acoustic system of microphones with an electronic/digital signal processing system. By using digital algorithms to process pickup signals and emulate microphone output, the system achieves comparable sound quality while reducing the complexity associated with physical microphone placement and acoustic management.
3Reliability
If acoustic pickups are used, then feedback resistance is improved, but sound quality deteriorates
Solution Approach 1:
The patent applies parameter changes to the pickup signal through digital signal processing. By adjusting frequency response, dynamics, and other audio parameters algorithmically, the system transforms the inherently limited pickup signal into output that emulates high-quality microphone sound, thus resolving the quality deficit while maintaining feedback resistance.
4Measurement precision
If signal processing algorithms are applied to pickup signals, then sound quality is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal signal processing system that can handle multiple pickup configurations and instrument types through a single algorithmic framework. This multi-functional approach improves sound quality across various applications while managing complexity through code reusability and standardized processing pipelines.
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 algorithm effectively reduces acoustic feedback and enhances sound quality, providing a reliable alternative to traditional microphone systems by processing pickup signals to emulate high-quality microphone outputs, improving sound reinforcement for acoustic instruments.
Implementation Method 1
One type of acoustic pickups make use of piezoelectric materials to convert mechanical vibrations into electrical current
Data Source
AI summary
A system and method is disclosed that facilitates the processing of a sound signal. In embodiments, an input sound signal can be processed according to a computational model using predetermined parameters. A sound signal originating from a musical instrument can be processed according to coefficients that are generated using a learning model.