Audio Authentication Using Gap-Embedded Hash Keys
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Solution Overview
Problem
There is an increase in voice-based authentication fraud due to the copying and cropping of audio clips for unauthorized transactions, necessitating effective protection and authentication of published audio files.
Innovation Solution
An audio file authentication system that extracts audio features, generates hash keys, and embeds them into audio gaps to create a processed audio file, using AI models to ensure authenticity and prevent manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If audio files are published on social media platforms, then visibility and communication effectiveness are improved, but vulnerability to voice-based authentication fraud increases
Solution Approach 1:
The system performs preliminary authentication by embedding hash keys into the audio file before publication. This preventive measure ensures that the audio file is protected against unauthorized copying and cropping before it becomes vulnerable to fraud on social media platforms.
Solution Approach 2:
The patent introduces hash keys as an intermediary element that mediates between the audio content and authentication verification. These hash keys serve as a digital signature that enables verification of the audio file's authenticity without interfering with the audio's communication function.
2Measurement precision
If hash keys are embedded into audio gaps, then authentication accuracy is improved, but audio file complexity increases
Solution Approach 1:
The system applies local quality by embedding hash keys specifically in the audio gaps rather than throughout the entire audio file. This targeted approach maintains high authentication accuracy while minimizing the impact on the overall audio file structure and usability.
Solution Approach 2:
The patent segments the audio file into speech segments and audio gaps, then selectively embeds hash keys only in the gaps. This segmentation strategy improves authentication precision without significantly complicating the audio file's practical structure.
3Reliability
If AI models are trained to adapt to age-related changes and noise, then authentication reliability is improved, but processing time and computational resources increase
Solution Approach 1:
The AI models are trained in advance on diverse datasets that include age-related voice changes and background noise. This preliminary training enables the models to quickly authenticate audio files in real-time without requiring extensive processing during actual authentication operations.
Solution Approach 2:
The system adapts authentication parameters based on detected voice characteristics, including age-related changes. By dynamically adjusting parameters rather than using fixed thresholds, the system maintains high reliability across different demographics while optimizing processing efficiency.
Data Source
AI summary
An audio file authentication system configured to extract a plurality of audio features for a plurality of raw audio files containing a digital recording of a specific user's voice, provide an authenticated audio file that includes a digital recording the specific user's voice based on the authentication information for the specific user, generate a parent hash key and sequential child hash keys that are unique to the authenticated audio file, and generate a processed audio file in which the parent hash key and each of the sequential child hash keys is inserted sequentially as data within the audio gaps of the audio file.