Voice Spectrogram Authentication for Secure User Verification
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Solution Overview
Problem
Existing systems lack the ability to authenticate user identity based on voice during voice calls, leading to unauthorized data interactions and resource wastage.
Innovation Solution
A system and method that generates a voice spectrogram from a user's voice call, extracts phonetic indicators, and compares them with historic spectrograms to authenticate the user's identity, using machine learning for verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If voice-based authentication is implemented, then data security is improved, but device complexity increases
Solution Approach 1:
The patent introduces voice spectrograms as an intermediary representation that mediates between the raw voice signal and the authentication decision. The spectrogram transforms the complex voice signal into a comparable visual representation, enabling secure authentication without requiring complex real-time voice analysis systems.
Solution Approach 2:
The patent creates a copy of the voice signal in the form of a spectrogram, which can be stored and compared against future voice inputs. This copying approach allows the system to authenticate users by comparing new spectrograms against stored historical spectrograms, improving security without requiring complex real-time processing.
2Reliability
If voice-based authentication is implemented, then unauthorized interactions are prevented, but processing resources are consumed
Solution Approach 1:
The patent performs preliminary action by generating and storing voice spectrograms during initial user registration or known good interactions. These pre-generated spectrograms are stored for future comparison, allowing the system to quickly authenticate users without consuming excessive processing resources during actual authentication events.
Solution Approach 2:
The patent compares only specific phonetic indicators extracted from the spectrograms rather than analyzing the entire voice signal. This partial action approach focuses computational resources on the most discriminative features, reducing overall processing requirements while maintaining high authorization accuracy.
3Measurement precision
If voice spectrogram comparison is performed, then user authentication accuracy is improved, but system complexity increases
Solution Approach 1:
The patent extracts specific phonetic indicators from the full voice spectrogram for comparison purposes. By taking out only the relevant phonetic features rather than comparing entire spectrograms, the system achieves high authentication accuracy while reducing the complexity of the comparison process.
Solution Approach 2:
The patent segments the voice authentication process into distinct stages: voice signal acquisition, spectrogram generation, phonetic indicator extraction, and comparison against stored templates. This segmentation allows each stage to be optimized independently, improving accuracy while managing system complexity through modular processing.
Data Source
AI summary
In response to receiving a voice call from a user, a new voice spectrogram is generated based on the voice of the calling user. A plurality of phonetic indicators are extracted from the new voice spectrogram and compared to phonetic indicators of a plurality of historic voice spectrograms associated with respective users. When a historic voice spectrogram includes one or more of the phonetic indicators extracted from the new voice spectrogram, it is determined that the identity of the calling user is authenticated. On the other hand, when none of the historic voice spectrograms include the one or more of the phonetic indicators extracted from the new voice spectrogram, it is determined that the identity of the calling user is not authenticated.