Mood-Based Media Interface Using Acoustic Analysis
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Solution Overview
Problem
Current media systems lack an effective user interface for efficiently accessing, managing, and playing media files based on mood categories, which limits user experience and interaction with media content.
Innovation Solution
A user interface generator that calculates a mood category for media files using acoustic data and presents a grid-based interface allowing users to select and interact with mood categories, enabling actions such as playlist generation and media playback through a touch-sensitive or voice-activated system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a traditional media file access interface is used, then the system structure remains simple, but the efficiency of accessing and managing media files by mood category is poor
Solution Approach 1:
The patent segments the media library into distinct mood categories (e.g., happy, sad, energetic, calm) and presents them as separate selectable groups in the user interface. This allows users to efficiently access media files by mood without navigating through entire libraries, thereby improving access efficiency while maintaining manageable system structure through logical organization.
Solution Approach 2:
The patent introduces a new organizational dimension (mood category) beyond traditional media file structures. By adding this categorical dimension and presenting it through a grid-based interface with visual indicators, the system enables efficient mood-based access without significantly complicating the underlying system architecture.
2Ease of operation
If a mood-based user interface is implemented, then the ease of operation for users is improved, but the device complexity increases due to acoustic analysis and interface generation components
Solution Approach 1:
The system performs preliminary acoustic analysis of media files during ingestion or idle periods, pre-categorizing them into mood groups before users need to access them. This preliminary processing enables instant mood-based navigation during user interaction, improving ease of operation while concentrating the computational complexity in background operations rather than real-time user interactions.
Solution Approach 2:
The patent introduces a mood category classification system as an intermediary layer between the raw media files and the user interface. This intermediary organizes media by acoustic mood characteristics and presents them through a simplified grid interface, thereby improving usability while containing complexity within the classification and presentation layer rather than throughout the entire system.
3Measurement precision
If acoustic data analysis is performed to determine mood categories, then the precision of mood classification is improved, but the energy consumption increases
Solution Approach 1:
The system performs acoustic analysis periodically or on-demand rather than continuously. Media files are analyzed for mood characteristics during idle periods, upon user request, or when first added to the library, rather than requiring constant real-time analysis. This periodic processing maintains classification accuracy while significantly reducing overall energy consumption compared to continuous analysis.
Solution Approach 2:
Acoustic mood analysis is performed in advance during media file ingestion or during system idle periods, so that when users need mood-based access, the classification is already complete. This preliminary action ensures precise mood categorization is available when needed while concentrating energy consumption in non-critical time periods rather than during active user interaction.
Data Source
AI summary
A user interface generator is configured to access a media file that stores acoustic data representative of sounds. The user interface generator determines a mood category of the media file, based on a mood vector calculated from the acoustic data. The mood category characterizes the media file as being evocative of a mood described by the mood category. The user interface generator generates a user interface that depicts a grid or map (e.g., a “mood grid” or a “mood map”) of multiple zones. One of the zones may occupy a position in the grid or map that corresponds to the mood category. The user interface may then be presented by the user interface generator (e.g., to a user). In the presented user interface, the zone that corresponds to the mood category may be operable (e.g., by the user) to perform one or more actions pertinent to the mood category.