Voice Stress Analysis Algorithm for Consistent Scoring
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Solution Overview
Problem
Existing voice stress analysis methods rely on human examiners for evaluating voice patterns, leading to inconsistencies due to fatigue, personal bias, and varying levels of training, which affects the accuracy and consistency of stress level scoring.
Innovation Solution
A computer-based system that analyzes voice patterns using software and algorithms to assign a numerical score indicative of psychological stress, eliminating human bias and ensuring consistent results by converting verbal utterances into electrical signals, filtering, and analyzing patterns to quantify stress levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human examiners manually evaluate voice patterns, then the system can provide expert judgment and interpretation, but the results become inconsistent due to fatigue, personal bias, and varying training levels
Solution Approach 1:
The patent replaces the mechanical system of human examination with an automated computer-based analysis system. The computer algorithm objectively measures voice pattern characteristics (frequency, amplitude, duration) and generates stress scores without human intervention, thereby eliminating variability introduced by examiner fatigue, bias, and training differences while maintaining measurement precision through systematic analysis.
Solution Approach 2:
The patent creates a digital copy of the voice evaluation process through software algorithms that replicate and standardize the analysis methodology. By encoding the evaluation criteria into computer-executable instructions, the system produces identical results for identical inputs regardless of who operates the system, ensuring reliability while preserving the expert judgment framework.
2Reliability
If a computer-based system is used to analyze voice patterns, then consistency and repeatability improve, but the system requires complex software algorithms and processing procedures
Solution Approach 1:
The patent segments the voice analysis process into distinct computational stages: signal acquisition, preprocessing (noise filtering, normalization), feature extraction (frequency, amplitude, duration parameters), pattern recognition (blocking detection), and score generation. This segmentation manages software complexity by organizing functions into modular components while ensuring reliable and consistent evaluation through systematic processing at each stage.
3Ease of operation
If voice patterns are converted into electrical signals and analyzed computationally, then the method becomes non-invasive and portable, but the system must accurately capture and process subtle vocal variations
Solution Approach 1:
The patent introduces an intermediary computational processing layer between the voice signal and the stress assessment. The software acts as a mediator that enhances subtle vocal variations through signal processing techniques (filtering, amplification, normalization) before analysis, making the non-invasive measurement method capable of detecting fine-grained voice pattern changes associated with psychological stress.
Data Source
AI summary
A system and method of assigning a numeric score to a voice pattern of a human subject wherein the score is indicative of the psychological stress level of the human subject. A verbal utterance of a human subject is converted into electrical signals to provide a subject wave pattern. The pattern is quantified and compared with known voice pattern characteristics which exhibit a sequential progression in the degree of blocking in the pattern, wherein each of the known voice patterns is assigned a numerical value range. A numerical value obtained from calculations is assigned to the subject wave pattern based on the comparison. The numerical value represents the degree of blocking present in the subject wave pattern which correlates to the amount of psychological stress exhibited by the human subject.