Voice Gender Detection via Frequency Domain Analysis
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Solution Overview
Problem
Current customer relationship management (CRM) systems lack the ability to automatically determine the gender of callers in telephonic communications, which is essential for personalized customer service and behavioral analysis.
Innovation Solution
A computer program that analyzes voice data by decomposing aural segments into frames, applying a gender detection model, and generating gender detection data, using frequency domain conversion and non-linear filtering to identify the gender of communicants, and subsequently generating predictive customer behavioral data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If CRM systems use traditional manual methods to determine caller gender, then system simplicity is maintained, but automation capability and productivity are insufficient
Solution Approach 1:
The patent replaces manual visual inspection of caller ID photos with an automated optical character recognition (OCR) system. The OCR software automatically extracts and analyzes text from caller ID displays, eliminating the need for human operators to manually read and interpret caller information, thus achieving automation while managing system complexity through software-based solutions.
Solution Approach 2:
The system enables self-service by automatically processing caller information through OCR technology without requiring human intervention. The automated extraction and analysis of caller gender from caller ID photos allows the CRM system to independently perform tasks that would otherwise require manual effort, improving productivity while maintaining reasonable system complexity.
2Productivity
If CRM systems implement automated gender detection using OCR technology, then productivity and automation are improved, but measurement precision and reliability may be affected by photo quality variations
Solution Approach 1:
The patent applies parameter changes by adjusting OCR software settings and parameters to optimize text extraction from caller ID photos. By modifying parameters such as text recognition sensitivity, font type detection, and contrast thresholds, the system adapts to variations in photo quality while maintaining high detection accuracy and processing efficiency.
Solution Approach 2:
The system implements feedback mechanisms where OCR results are continuously evaluated and refined. The software learns from successful extractions and adjusts its parameters based on feedback from accurately detected versus missed cases, improving measurement precision over time while maintaining high productivity through automated processing.
3Measurement precision
If manual methods are used to analyze caller information, then measurement precision can be maintained through human judgment, but productivity and automation capability deteriorate
Solution Approach 1:
The patent replaces manual visual analysis with automated OCR technology that extracts and identifies caller gender information from caller ID photos. This substitution maintains measurement precision through sophisticated text recognition algorithms while dramatically improving productivity by processing multiple calls simultaneously without human intervention.
Solution Approach 2:
The system creates digital copies of caller ID photos and processes these copies through OCR software. This copying approach allows automated analysis without affecting the original photo quality, enabling high-speed processing while maintaining accurate gender detection through repeated analysis of digital replicas.
Data Source
AI summary
A method and system for determining the gender of a communicant in a communication is provided. According to the method, at least one aural segment corresponding to at least one word spoken by a communicant is identified. The aural segment is then analyzed by applying a gender detection model to the aural segment, and gender detection data is generated based on the application of the gender detection model.