Voice Signal Alcohol Detection via FFT Spectral Slope Analysis
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Solution Overview
Problem
Existing methods for determining alcohol consumption are not suitable for remote locations, as they require direct contact and are not effective in detecting alcohol consumption without the operator's consent, posing risks in vehicular and aviation operations.
Innovation Solution
A method that analyzes voice signals using fast Fourier transforms to determine alcohol consumption by comparing the energy difference between the original and difference signals in the frequency domain, allowing for remote and objective assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct testing methods (breathalyzer or blood test) are used to determine alcohol consumption, then measurement precision is improved, but ease of operation deteriorates because direct contact with the operator is required
Solution Approach 1:
The patent uses voice signals as an intermediary to indirectly determine alcohol consumption. Instead of directly testing the operator with breathalyzers or blood tests, the system captures voice signals transmitted over communication channels and analyzes them for alcohol consumption indicators, thereby avoiding direct contact while maintaining measurement capability
Solution Approach 2:
The patent replaces mechanical/physical testing systems (breathalyzer devices, blood collection procedures) with an acoustic analysis system. By substituting the mechanical testing apparatus with voice signal processing and frequency analysis, the system achieves alcohol consumption detection without requiring physical testing equipment or direct operator contact
2Ease of operation
If voice analysis method is used to determine alcohol consumption remotely, then ease of operation is improved, but measurement precision deteriorates due to indirect assessment
Solution Approach 1:
The patent transitions from time-domain voice signals to frequency-domain analysis using Fast Fourier Transform. By converting the voice signal representation from temporal to spectral domain, the system can extract frequency-based features (formant slopes, spectral characteristics) that are more sensitive to alcohol consumption effects, thereby improving measurement precision while maintaining remote operation capability
Solution Approach 2:
The patent changes the analysis parameters from general voice characteristics to specific frequency-domain parameters such as formant slopes and spectral energy distribution. By focusing on these specific parameters that are known to change with alcohol consumption, the system improves measurement precision while keeping the operation simple and remote
3Measurement precision
If multiple effective frames are used in analysis, then measurement precision is improved, but loss of time increases due to additional processing
Solution Approach 1:
The patent performs preliminary processing by pre-identifying and extracting effective frames (voiced sound frames) from the voice signal before main analysis. By preparing and filtering the relevant frames in advance, the system can use multiple frames for improved precision without excessive time penalty, as the filtering and selection are done efficiently beforehand
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
Enables accurate determination of alcohol consumption from a distance, increasing accuracy with multiple effective frames and preventing accidents caused by drunk operation, applicable in various transportation sectors.
Implementation Method 1
performing fast Fourier transforms on the original signal and the difference signal
Data Source
AI summary
An alcohol consumption determination method includes: detecting an effective frame of an input voice signal; detecting a difference signal of an original signal of the effective frame; performing fast Fourier conversion on the original signal and the difference signal; and determining, in the frequency domain, whether alcohol has been consumed based on a slope difference between the fast-Fourier-transformed original signal and the fast-Fourier-transformed difference signal. Accordingly, it is also possible to determine whether a driver or an operator from a remote location has consumed alcohol and a degree of the consumption, thus preventing an accident caused by an individual operating a vehicle under the influence.


