Voice Spectrum Analysis for Secure Speaker Identification
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Solution Overview
Problem
Existing biometric identity recognition and verification systems face security risks due to digitization of data, which can be copied or compromised, and multi-step verification processes are not user-friendly.
Innovation Solution
A speaker identification system using vocal spectrum analysis that collects and processes voice samples to generate unique patterns for enrollment and verification, incorporating sub-spectra analysis, formant vectors, and harmonic comparisons to enhance security and detect spoofing attempts, while allowing for convenient user access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If biometric data is digitized for identity recognition, then implementation cost is reduced and processing efficiency is improved, but security level decreases because digitized data can be copied or compromised
Solution Approach 1:
The system performs preliminary voice spectrum analysis during the enrollment phase to capture unique vocal characteristics before any verification occurs. This advance preparation creates a reference pattern that can be quickly compared during verification, improving processing efficiency while maintaining security through sophisticated spectral analysis
Solution Approach 2:
The system transforms voice samples from time-domain signals to frequency-domain representations using spectral analysis. By changing the parameter domain from temporal to spectral, the system creates a more secure biometric representation that captures unique vocal characteristics while enabling efficient pattern matching
2Reliability
If multi-step verification process is implemented to combat security risks, then security level is improved, but user convenience decreases
Solution Approach 1:
The system merges multiple verification characteristics (formant frequencies, harmonic structures, spectral envelope) into a single integrated voice spectrum analysis process. This consolidation maintains high security by analyzing multiple parameters simultaneously while presenting a simple, convenient interface to users
Solution Approach 2:
The voice spectrum analysis system serves multiple functions: enrollment, verification, and spoofing detection, all through a single unified process. This multi-functionality eliminates the need for separate verification steps while maintaining comprehensive security checks
3Reliability
If voice samples are processed into detailed sub-spectra for spoof detection, then security level is improved, but processing complexity increases
Solution Approach 1:
The system segments the frequency spectrum into multiple sub-spectra bands, analyzing different frequency ranges separately. This segmentation enables detailed spoofing detection by examining harmonic structures in different bands while organizing the processing complexity into manageable, structured segments
Data Source
AI summary
Hardware and/or software systems, devices, networks, and methods for identity recognition and verification based on vocal spectrum analysis. The system including one or more processors coupled to a memory/storage to collect audio samples sufficient to generate a speaker identification reference pattern and a speaker identification verification pattern, generate a speaker identification reference pattern from the audio samples and a speaker identification verification pattern from other audio samples, compare the speaker identification verification pattern with the speaker identification reference pattern; and provide a response indicating whether the speaker identification verification pattern and the speaker identification reference pattern were generated based on audio samples from the same person. The system may be employed on a mobile phone in near field communication with a control system and may include a management platform.