Music File Classification Using Mood Vectors and Color Display
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Solution Overview
Problem
Consumer electronic devices struggle to accurately classify music files based on user-perceived similarity, leading to suboptimal playlist generation and selection experiences.
Innovation Solution
A method and graphical interface for consumer electronic devices that calculate mood-related vectors and display music files in a mood plane, allowing users to select and classify music files based on perceptual attributes like tempo, rhythm, and genre, using a calculator unit to determine classification information and display it in a user-friendly manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If music files are classified using traditional preset categories (genre, mood, interpreter), then playlist generation is automated, but the classification results do not align with user-perceived similarity
Solution Approach 1:
The patent transforms music classification from traditional categorical dimensions (genre, mood, interpreter) to a perceptual similarity dimension represented by color vectors. Each music file is assigned a color based on its acoustic characteristics, and files with similar colors are perceived as similar by users. This dimensional transformation resolves the contradiction by creating a new classification space that directly reflects user perception rather than relying on preset categories that may not align with how users actually perceive musical similarity.
2Measurement precision
If more music attributes are analyzed for classification, then classification precision improves, but device complexity increases
Solution Approach 1:
The patent extracts the essential perceptual characteristics of music files and represents them as color vectors, eliminating the need to process and compare multiple complex music attributes directly. Instead of analyzing numerous attributes separately, the system extracts a condensed color representation that captures the essential similarity information, thereby reducing computational complexity while maintaining or improving classification precision.
Solution Approach 2:
The patent changes the parameter representation from multiple discrete music attributes (tempo, rhythm, genre, etc.) to a continuous color vector parameter space. This parameter transformation allows for more efficient comparison and classification, as color values provide a intuitive and computationally simple way to represent and compare musical similarity across multiple dimensions simultaneously.
3Ease of operation
If a visual display interface is provided for music selection, then user experience improves, but information display complexity increases
Solution Approach 1:
The patent uses color as a visual metaphor to represent music file similarity. Each music file is displayed with a color corresponding to its color vector, allowing users to visually identify similar files through color matching. This color-based visualization simplifies the interface by providing an intuitive and aesthetically pleasing way to navigate and select music files based on perceptual similarity, avoiding complex traditional metadata displays while enhancing user experience.
Data Source
AI summary
At an apparatus (200), which may be a consumer electronic device, the user may select a predetermined number of different music attributes (Attr) descriptive of a mood delivered by music represented by music content of a music file. From parameters of a music file available in the apparatus (200), the apparatus (200) determines a first vector (m1(Dat)) descriptive of a relationship between the music content and all selected music attributes (Attr) and a second vector (m2(Dat)) and outputs a classification information related to the music file and containing the first and second vectors (m1(Dat), m2(Dat)). The classification information may be used to assign a colour to a displayed object assigned to the music file. Perceptually similar music files may be displayed in similar colours.


