Context-Aware Audio Muting and Program Blocking
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Solution Overview
Problem
Current V-Chip technology only allows for categorical blocking of television programs based on ratings, failing to provide granular control, such as blocking specific programs or muting context-specific words, which can be offensive in certain contexts but not others.
Innovation Solution
A method for blocking or muting television programs based on customizable criteria, including program-specific information, ratings, and context-specific words, allowing users to block or mute programs containing objectionable words by analyzing their usage in different contexts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If V-Chip technology is used for program blocking, then categorical blocking based on ratings is achieved, but granular control over specific programs or context-specific words is lost
Solution Approach 1:
The patent segments the program content control into multiple independent filtering layers: rating-based blocking, program-specific blocking, and word-level filtering. This allows granular control over different aspects of content without requiring a completely new system, thus improving adaptability while managing complexity through modular architecture.
Solution Approach 2:
The system integrates multiple control functions into a single unified platform that can perform rating-based blocking, program-specific blocking, and context-aware word filtering. This multi-functional approach improves versatility without proportionally increasing complexity, as the same infrastructure supports multiple control granularities.
2Object-affected harmful factors
If all programs with TV-14 rating are blocked, then sexually charged content is filtered, but other acceptable TV-14 programs are also blocked
Solution Approach 1:
The patent applies local quality filtering by allowing different blocking rules for different programs. Instead of uniform blocking for all TV-14 content, the system can identify specific programs (like Coupling) that contain objectionable content and block only those, while allowing other TV-14 programs to pass through. This is achieved by analyzing program metadata and content characteristics to apply selective filtering.
Solution Approach 2:
The system dynamically adjusts blocking criteria based on program identification. When a specific program is detected (through metadata matching), the blocking rule is activated; when a different program is detected, the rule is deactivated. This dynamic behavior allows the system to transition between blocking and allowing states based on real-time program identification, providing selective control.
3Object-affected harmful factors
If words are blocked without context analysis, then objectionable words are filtered, but contextually acceptable uses of words are also blocked
Solution Approach 1:
The system performs preliminary analysis of program metadata, episode descriptions, and content characteristics before applying word filtering. By pre-characterizing programs and their content themes, the system can make more accurate determinations about whether a word should be blocked, improving contextual accuracy before the actual filtering occurs.
Solution Approach 2:
The system uses feedback from program metadata and content analysis to adjust word filtering decisions. When a program is identified as having specific content characteristics (e.g., children's programming, educational content), the system modifies its word blocking behavior accordingly. This feedback loop allows the system to learn from program context and make more precise filtering decisions.
4Measurement precision
If context analysis is performed to determine word usage, then filtering accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of program metadata, episode descriptions, and content characteristics before applying word filtering. By pre-characterizing programs and their content themes, the system can make more accurate determinations about whether a word should be blocked, improving contextual accuracy before the actual filtering occurs.
Solution Approach 2:
The system applies partial context analysis rather than complete context analysis for all words. Instead of analyzing every word in every program, the system focuses context analysis on specific words that appear in objectionable content lists, and only performs deep contextual analysis when necessary. This partial action approach maintains reasonable filtering accuracy while significantly reducing processing time.
Data Source
AI summary
A program blocking application that blocks programming for one or more possible users, based on various criteria associated with the program. A program word muting application that selectively mutes context specific words as a function of program specific criteria.


