Audio Filtering via Caption Timestamps
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Solution Overview
Problem
Current media devices lack the ability to efficiently and accurately filter out inappropriate audio content based on user preferences or cultural sensitivities, leading to unpleasant experiences for viewers, especially when children and adults watch media together.
Innovation Solution
A system that receives filtering instructions from users, using text or voice inputs, to identify and remove specific audio content from media tracks based on timestamp correspondence with captioning data, employing machine-learning models to determine audio fingerprints and customize filtering content for different audiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional media devices play audio content without filtering, then the audio content is complete and uninterrupted, but inappropriate content may be heard by all audiences regardless of age or sensitivity
Solution Approach 1:
The audio track is segmented into multiple components including voice portions, music portions, and sound effect portions. The system processes each segment separately, applying filtering only to relevant portions (e.g., muting inappropriate voice content while preserving music and sound effects), thereby reducing the impact on overall audio quality while enabling targeted filtering.
Solution Approach 2:
Captioning data serves as an intermediary element that bridges the user's filtering preferences and the actual audio content. The system searches captioning data for filtering content and uses timestamp correspondence to identify and filter matching audio portions, enabling accurate filtering without direct complex analysis of the audio signal itself.
2Adaptability or versatility
If the system filters audio content based on user preferences, then personalized filtering is achieved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by searching for filtering content in the captioning data before processing the audio track. By pre-identifying filtering content and its corresponding timestamps from the captioning data, the system prepares the filtering criteria in advance, enabling faster real-time audio processing without extensive analysis during playback.
Solution Approach 2:
The system replaces complex mechanical audio analysis with a more efficient information processing approach. Instead of analyzing audio signals directly to identify filtering content, the system substitutes this with text-based searching of captioning data and timestamp-based audio track identification, significantly reducing computational complexity and processing time.
3Measurement precision
If the system uses audio fingerprinting to identify filtering content, then accurate identification is achieved, but the computational complexity and processing overhead increase
Solution Approach 1:
Captioning data acts as an intermediary that simplifies the identification process. Instead of directly analyzing complex audio signals to identify filtering content, the system searches for filtering content in the text-based captioning data first, then uses timestamp correspondence to locate and filter the corresponding audio portions, reducing the need for complex audio fingerprinting operations.
Solution Approach 2:
The system extracts filtering content identification from the complex audio signal analysis domain and relocates it to the simpler text processing domain. By extracting filtering content keywords from captioning data and using timestamps to map back to audio, the system separates the identification function from the audio processing function, reducing overall system complexity.
Data Source
AI summary
Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for automatically filtering out audio in an audio track of a content. An example embodiment operates by receiving a filtering instruction for a media device, identifying a filtering content in an audio track of a content to be presented on the media device based on the filtering instruction, filtering out the filtering content in the audio track of the content, and presenting the filtered content on the media device.