Speaker-Specific Spoken Passwords Using Unique Speech Features
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Solution Overview
Problem
Conventional spoken password systems are vulnerable to security breaches when impostors obtain pre-learned passwords, as they do not dynamically adapt to the unique speech features of legitimate users.
Innovation Solution
A method and apparatus for generating speaker-specific spoken passwords by identifying and incorporating distinctive speech features that distinguish a speaker of interest from impostors, using a system comprising an input device, preprocessor, feature selection processor, speaker model generator, and output device to create a customized password based on unique phonemes and prosodic behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-learned static spoken passwords are used, then ease of operation is improved, but reliability deteriorates due to security vulnerabilities when impostors obtain the passwords
Solution Approach 1:
The patent transforms static spoken passwords into dynamic speaker-specific passwords by incorporating speaker identification technology. The system continuously adapts to the legitimate user's speech patterns and automatically updates the password criteria, making the authentication system dynamic rather than static. This resolves the contradiction by maintaining ease of use while improving security through adaptive verification.
Solution Approach 2:
The patent changes the parameters of the password system by shifting from content-based verification to speaker-characteristic-based verification. It analyzes multiple speech parameters including pitch, tone, rhythm, and spectral characteristics to create a multi-dimensional authentication system. This parameter transformation maintains user convenience while significantly enhancing security against impostors.
2Reliability
If speaker-specific speech features are analyzed and incorporated, then reliability is improved through enhanced security, but device complexity increases
Solution Approach 1:
The patent implements a self-training mechanism where the system automatically learns and adapts to the legitimate user's speech patterns without requiring manual configuration or complex setup procedures. The speaker model generator continuously refines the authentication criteria based on ongoing interactions, enabling the system to self-optimize security parameters while maintaining operational simplicity.
Solution Approach 2:
The patent replaces complex mechanical or manual security verification systems with acoustic and signal processing techniques. By using digital signal analysis and machine learning algorithms to extract speaker features, the system achieves high security reliability through software-based solutions rather than complex hardware mechanisms, thereby reducing overall system complexity.
3Device complexity
If conventional static passwords are used, then device complexity is minimized, but object-generated harmful factors increase due to security breaches
Solution Approach 1:
The patent performs preliminary speaker characterization and model generation during an initial training phase before actual authentication begins. By pre-learning the legitimate user's speech patterns and establishing baseline speaker models in advance, the system prepares security defenses proactively. This preliminary action enables the system to detect and prevent security breaches before they occur, addressing harmful factors in advance while maintaining operational simplicity.
Data Source
AI summary
The present invention relates to a method and apparatus for generating speaker-specific spoken passwords. One embodiment of a method for generating a spoken password for use by a speaker of interest includes identifying one or more speech features that best distinguish the speaker of interest from a plurality of impostor speakers and incorporating the speech features in the spoken password.