Music Playback System Using Attribute-Based Pairing for Thematic Coherence
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Solution Overview
Problem
Existing music playback methods, such as shuffling and mashups, often result in non-random and irrelevant music playback due to algorithmic patterns, disrupting the user's intended playlist flow and theme, failing to provide the desired listening experience.
Innovation Solution
A method that creates a playing pool of playlists with attributed music, comparing attributes to identify 'pairing music' across playlists, allowing seamless switching between similar tracks based on user-defined attributes like singer, song, album, or genre, ensuring continuous playback of desired music.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If shuffle feature is used to avoid repeated listening, then music variety is improved, but the playback becomes non-random and still results in certain repeated playing due to algorithmic patterns
Solution Approach 1:
The system dynamically adjusts playback behavior by switching between different playback modes (sequential, shuffle, smart shuffle) based on user context and playlist characteristics. The smart shuffle mode dynamically selects tracks from paired playlists based on attribute matching, creating an adaptive playback experience that balances variety and unpredictability.
Solution Approach 2:
The system changes the parameter of track selection by introducing attribute-based pairing between playlists. Instead of pure random selection, tracks are selected based on matching attributes (genre, mood, tempo, etc.), transforming the selection criterion from completely random to attribute-guided random, thereby improving both variety and perceived randomness.
2Adaptability or versatility
If mashup is used to mix tracks from multiple playlists, then music variety is improved, but the flow of listening experience is broken and thematic coherence is lost
Solution Approach 1:
The system applies local quality by maintaining thematic coherence within each playlist while introducing variety through attribute-based pairing. Tracks are selected from paired playlists based on matching local attributes (genre, mood, tempo), ensuring that each selected track fits the local thematic context while still providing variety from multiple sources.
Solution Approach 2:
The system uses attribute matching as an intermediary mechanism between multiple playlists. Instead of directly mixing tracks from different themes (which breaks coherence), the attribute matching acts as a mediator that ensures only thematically compatible tracks are selected, preserving overall listening flow while enabling variety.
3Adaptability or versatility
If pure random playback is used, then unpredictability is improved, but the music played may be completely irrelevant to user preferences
Solution Approach 1:
The system changes the selection parameter from completely random to attribute-based probabilistic selection. Tracks are selected based on matching attributes with the currently playing track, creating a controlled randomness that maintains relevance to user preferences while preserving unpredictability and variety.
Solution Approach 2:
The system uses attribute matching as a feedback mechanism to guide track selection. The attributes of the currently playing track provide feedback for selecting the next track, ensuring that the selection process remains relevant to user preferences while still introducing variety through the random selection among matching candidates.
Data Source
AI summary
A method of playing music includes providing a playing pool, where the playing pool includes a plurality of playlists, each playlist includes at least one piece of music, and each piece of music includes at least one attribute; comparing all music in any two playlists, and if at least one attribute of any two pieces of music is determined to be identical, defining the music as pairing music, where the pairing music is not music the same playlist; and playing the music in one of the plurality of playlists, and when a playing sequence comes to the pairing music, playing the music according to the pairing music.