Digital Audio Content Filtering With Personalized Word Replacement
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Solution Overview
Problem
Existing methods for filtering objectionable content in real-time, such as during live events, are impractical and do not account for individual preferences, as they either delete or 'bleep out' content uniformly without considering personal objections.
Innovation Solution
A system that processes audio and video signals to identify and remove specific words or phrases by translating audio blocks into text, comparing them to a prohibited word database, and replacing them with silence or alternative sounds based on offset and duration values, allowing for personalized content filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is deleted or bleeped out uniformly, then objectionable content is removed, but individual preferences are not considered and live events cannot be filtered in real-time
Solution Approach 1:
The audio signal is divided into discrete blocks, and each block is independently processed through speech-to-text conversion and prohibited word comparison. This segmentation enables real-time filtering by handling small units sequentially rather than attempting to process the entire audio stream at once, making the system manageable and adaptable to individual preferences.
Solution Approach 2:
A prohibited word database serves as an intermediary between the audio input and the filtering decision. The database stores user-defined objectionable words and phrases, allowing the system to adapt to individual preferences without complex decision logic. The database mediates the comparison process, enabling personalized filtering while keeping the processing system relatively simple.
2Measurement precision
If speech-to-text conversion and word comparison are performed for each audio block, then personalized filtering is achieved, but processing time and computational resources increase
Solution Approach 1:
By segmenting the audio into small blocks and processing them sequentially, the system maintains measurement precision through careful comparison of each block's transcribed words against the prohibited database, while managing processing time by handling only one block at a time rather than the entire audio stream simultaneously.
Solution Approach 2:
The system performs speech-to-text conversion and comparison for each audio block, which may seem like excessive action, but this partial processing approach ensures high accuracy for each segment while the cumulative effect across blocks achieves real-time filtering. The excessive scrutiny of each individual block translates to overall system efficiency through modular processing.
Data Source
AI summary
According to some embodiments, content filtering is provided for a digital audio signal.