Voice Word Recognition for Selective Offensive Content Filtering
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Solution Overview
Problem
Existing audio-video content filtering systems require specialized hardware, are costly, and lack the ability to selectively modify objectionable content, often leading to inaccurate filtering and inability to replace objectionable material with less-objectionable alternatives.
Innovation Solution
A voice-based word recognition system that detects and selectively modifies offensive words or phrases by analyzing audio input, generating alerts, and implementing modifications such as muting, bleeping, or replacing the offensive content before transmission, utilizing machine learning for improved accuracy and real-time processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If specialized hardware is used for content filtering, then filtering reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces specialized hardware filtering systems with software-based voice recognition and analysis processing. The system uses voice-based detection algorithms running on general-purpose computing devices to identify and filter offensive content, eliminating the need for dedicated filtering hardware while maintaining effective content monitoring capabilities
Solution Approach 2:
The system creates a software-based copy of the filtering function that can operate on standard computing platforms. By implementing voice recognition and content analysis as software rather than hardware, the filtering capability can be replicated across different devices without requiring specialized hardware components
2Object-affected harmful factors
If the entire program is blocked due to offensive content, then harmful factors are reduced, but loss of information increases
Solution Approach 1:
The system extracts and identifies only the specific offensive words or phrases from the audio content using voice recognition technology. Instead of blocking the entire program, it selectively targets and removes only the harmful portions while allowing the rest of the content to pass through unchanged, thereby minimizing information loss
Solution Approach 2:
The filtering is applied locally to specific detected offensive segments rather than globally to the entire content stream. The system modifies only the portions of audio containing offensive content while leaving other segments intact, enabling selective censorship that preserves valuable information
3Productivity
If real-time voice analysis is implemented, then productivity is improved, but use of energy increases
Solution Approach 1:
The system performs partial voice analysis by focusing computational resources only on detecting specific voice patterns and keywords rather than analyzing every aspect of the audio signal in real-time. This selective approach enables real-time processing while reducing overall energy consumption compared to comprehensive audio analysis
Data Source
AI summary
A voice-based word recognition device, system, and methods are provided for detecting and selectively modifying offensive words. The voice-based word recognition system may be used to monitor and receive signal data from an input/output source. The system may include a voice-based word detector configured to identify a potentially offensive word or phrase from the received signal data. The system may be implemented to analyze whether the identified potentially offensive word or phrase matches an offensive word or phrase from a list of predetermined words. The system may then generate alert data in response to the identified potentially offensive word or phrase matching the offensive word or phrase. As such, the system may therefore modify the matched offensive word or phrase in response to the generated alert data, such that the matched offensive word or phrase is thereby modified prior to audio output data being generated and transmitted to external users.