Audio Player Explicit Lyric Removal via Metadata Segmentation
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Solution Overview
Problem
Current audio devices and services can only block entire songs with explicit content, requiring users to obtain separate 'clean' versions, which is inconvenient and inefficient.
Innovation Solution
An audio player can identify and remove explicit audio during playback by using metadata or real-time recognition analysis, replacing it with alternate audio such as beeps or silence, allowing seamless switching between clean and explicit versions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If entire songs with explicit lyrics are blocked, then explicit content is removed, but user access to the song is completely prevented
Solution Approach 1:
The audio stream is segmented into explicit and non-explicit portions based on metadata or real-time analysis. The system then selectively removes only the explicit segments while preserving the rest of the song, allowing users to access the full track without requiring separate clean versions. This resolves the contradiction by enabling partial content removal rather than complete blockage.
Solution Approach 2:
The explicit portions are extracted from the audio stream using metadata indicators or real-time recognition, and these specific segments are removed or replaced with alternate audio. This extraction approach allows the majority of the song to remain accessible, balancing content removal with user accessibility.
2Object-affected harmful factors
If separate clean versions of songs are provided, then explicit content is removed, but device complexity and storage requirements increase
Solution Approach 1:
The system merges the original explicit audio stream with metadata or real-time analysis capabilities within a single file structure. Instead of maintaining separate clean and explicit versions, the system combines the original audio with removal instructions or dynamic analysis, reducing storage requirements and simplifying file management while still enabling explicit content removal.
Solution Approach 2:
Rather than creating complete copies of clean versions, the system creates only the necessary metadata or analysis data that describes where explicit content occurs. This copying approach stores minimal information (time stamps, duration) rather than full audio tracks, significantly reducing device complexity and storage needs.
3Object-affected harmful factors
If real-time recognition analysis is used, then explicit content is identified during playback, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary action by analyzing audio streams beforehand or using pre-generated metadata that indicates explicit content locations. This advance preparation allows the actual playback to proceed without continuous real-time processing, reducing computational burden and processing time while still achieving accurate explicit content identification.
Solution Approach 2:
Instead of continuously analyzing every audio sample in real-time, the system applies partial action by using metadata indicators or analyzing only at specific intervals. This partial approach reduces processing requirements while maintaining sufficient accuracy for explicit content removal, balancing identification effectiveness with processing efficiency.
Data Source
AI summary
Unwanted audio, such as explicit language, may be removed during audio playback. An audio player may identify and remove unwanted audio while playing an audio stream. Unwanted audio may be replaced with alternate audio, such as non-explicit lyrics, a “beep”, or silence. Metadata may be used to describe the location of unwanted audio within an audio stream to enable the removal or replacement of the unwanted audio with alternate audio. An audio player may switch between clean and explicit versions of a recording based on the locations described in the metadata. The metadata, as well as both the clean and explicit versions of the audio data, may be part of a single audio file, or the metadata may be separate from the audio data. Additionally, real-time recognition analysis may be used to identify unwanted audio during audio playback.