Voice Recording Security Masking via Speech Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for securing sensitive information in voice recordings are inefficient and economically impractical, as they rely on manual monitoring and deletion, which is not feasible for the large volume of data being generated, and there is no uniform definition of sensitive information across different settings.
Innovation Solution
The method involves using speech recognition to process voice recordings, identifying sensitive information through a prompt list, and rendering those segments unintelligible or encrypting them, with optional metadata to indicate processing status, allowing secure transfer of recordings without unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring and deletion of sensitive information is used, then security of sensitive information is improved, but productivity and cost-effectiveness deteriorate due to the large volume of data
Solution Approach 1:
The patent replaces manual mechanical review processes with automated speech recognition technology. The system uses speech-to-text conversion followed by automated text analysis to identify sensitive information, eliminating the need for human reviewers to manually listen to and analyze each recording, thereby dramatically improving processing efficiency while maintaining security.
Solution Approach 2:
The system enables self-service automation where the speech recognition system automatically identifies, flags, and redacts sensitive information without human intervention. The automated workflow includes transcription, sensitive information detection, and redaction execution, allowing the system to service itself in protecting sensitive data across large volumes of recordings.
2Productivity
If speech recognition automation is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex speech recognition and analysis system into distinct functional modules: speech-to-text transcription module, sensitive information detection module, and redaction module. This segmentation allows each component to be developed, tested, and maintained independently, managing overall system complexity while achieving high productivity through automated processing.
3Ease of operation
If uniform definition of sensitive information is applied across all settings, then ease of operation is improved, but adaptability deteriorates due to context-specific variations
Solution Approach 1:
The patent implements a dynamic configuration system where the definition of sensitive information can be adjusted based on contextual requirements. The system allows administrators to define context-specific sensitive information categories (e.g., medical records for healthcare, financial data for banking) while maintaining a uniform operational framework. This dynamic adaptability enables the same system to serve multiple industries and contexts without sacrificing ease of operation.
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
Apparatuses and methods are described to secure information contained within voice recordings. A voice recording (step 102) is loaded into a data processing system (100), wherein the voice recording results from an utterance of a human during an interaction between the human and an interface of a business entity. The voice recording is processed to recognize at least one element of text in the voice recording (step 104). The data processing system determines if the at least one element of text represents special information that pertains to the human (step 106). A segment in the voice recording is rendered unintelligible if the at least one element of text represent special information that pertains to the human (step 108-112).