Signal Matching Using Parameter Eta for Audio Classification
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Solution Overview
Problem
Existing technologies lack effective methods for signal matching and segment/type judgment using the parameter η, which is a shape parameter for a generalized Gaussian distribution in audio signal processing.
Innovation Solution
A matching device and judgment device that utilize the parameter η to determine the degree of match or type of a signal by processing whitened spectral sequences, allowing for efficient signal classification and segmentation based on the parameter η's shape characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LSP (Line Spectrum Pair) is used as a parameter for sound classification and segment estimation, then the parameter provides comprehensive spectral information, but it becomes difficult to perform processing based on threshold values due to having multiple values
Solution Approach 1:
The patent extracts a single representative value (mean value) from the multiple LSP parameters to create a simplified parameter η. This extraction process retains the essential spectral information while converting the multi-dimensional LSP data into a single scalar value that can be easily processed with threshold-based methods, directly resolving the contradiction between comprehensive spectral information and ease of threshold processing
Solution Approach 2:
The patent transforms the LSP parameter through a mathematical transformation to create a new parameter η with different characteristics. By changing the parameter representation from multiple spectral values to a single shape parameter, the system maintains the ability to characterize spectral properties while enabling simpler threshold-based operations
2Loss of information
If multiple LSP values are used for signal analysis, then the spectral characteristics are well-represented, but the processing complexity increases compared to single-value parameters
Solution Approach 1:
The patent extracts the essential spectral characteristic information from multiple LSP values by computing a single representative parameter η. This extraction maintains the critical spectral shape information needed for signal analysis while eliminating the complexity of processing multiple individual LSP values, thus reducing processing complexity without significant information loss
Data Source
AI summary
A matching device includes a matching unit that judges, based on a first sequence of parameters η corresponding to each of at least one time-series signal of a predetermined time length which makes up a first signal and a second sequence of the parameters η corresponding to each of at least one time-series signal of the predetermined time length which makes up a second signal, the degree of match between the first signal and the second signal and/or whether or not the first signal and the second signal match with each other.