Nonlinear System Modeling via Frequency Response Profiling
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Solution Overview
Problem
Existing methods for modeling the characteristics of musical instruments are limited in accurately capturing the frequency response and timbre of entire instruments, particularly in non-linear regions, requiring large memory spaces and restrictive database approaches.
Innovation Solution
A method involving feeding testing input signals into the instrument to identify significant changes in output levels and energy differences across frequency bands, allowing for the derivation of response characteristics and modeling of the instrument's characteristics, including the use of sweep signals and amplitude modulation to improve noise robustness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical sound modeling with instrument models is used to characterize sound parameters at their mechanical/acoustic source, then the quality and throughput of synthesized sounds are improved, but large memory space is required to store the models
Solution Approach 1:
The patent transforms the physical sound modeling approach by changing from storing complete instrument models to storing and processing only relevant acoustic parameters (transfer function, frequency response, timbre characteristics). This parameter transformation enables high-quality sound synthesis with reduced memory requirements, as the system processes acoustic parameters rather than storing entire instrument models.
2Adaptability or versatility
If a database of analyzed data is built to characterize the whole instrument, then new sounds can be synthesized, but the approach is restrictive to isolated tones and requires large memory space
Solution Approach 1:
The patent extracts the essential acoustic characteristics from complete instrument models by identifying and isolating key parameters such as transfer function, frequency response, and timbre. This extraction process removes unnecessary data while retaining the core information needed for sound synthesis, enabling versatile sound generation without storing entire instrument databases.
Solution Approach 2:
The system transforms the approach by changing from storing comprehensive instrument databases to processing extracted acoustic parameters. This parameter-based approach maintains adaptability for synthesizing various sounds while significantly reducing memory requirements, as only essential acoustic characteristics are stored and manipulated.
3Measurement precision
If reference profile analysis is used to evaluate the characteristic frequency response, then the sound impression can be matched, but the method does not precisely estimate frequency response of the entire musical instrument including filter and amplification stages
Solution Approach 1:
The patent introduces an intermediary analysis process that bridges the gap between reference profile matching and complete instrument characterization. The system uses the reference profile as an intermediary step to identify acoustic parameters, then combines these with separate measurements of filter and amplification stages to achieve comprehensive frequency response estimation, thus recovering the information lost in simple reference matching.
Data Source
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Figure 4~5
AI summary
A method of modeling (fig. 4, fig. 5) a characteristic of a non-linear system (21), comprises feeding test input signals (Sig6, Sig7) into the non-linear system (21) to obtain test output signals (Resp6, Resp7), wherein the test input signals (Sig6, Sig7) include a first test input signal (Sig6) and the test output signals (Resp6, Resp7) include a first test output signal (Resp6), identifying occurrences when an output level in at least one specific frequency band of the first testing output signal significantly changes under the first test input signal (e.g. identifying the frequencies at which there are overtones) so as to obtain a first profile (Profile B: frequency index versus input level, fig. 7), and modeling the characteristic (e.g. frequency response of pre-amplifier stage, fig. 8) based on the first profile (fig. 20). Various test input signals may be used : Amplitude sweep (fig. 6a-c), frequency sweep (fig. 10), white noise or chirp signal. The breakup point of overtones onsets in the table of frequency bins versus input signal is determined. The application of this profile to model the non-linear amplifier stage of a music instrument, for instance a guitar, is also defined.