Emotion-Based Music Distribution Using Image Recognition
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Solution Overview
Problem
Conventional music distribution systems fail to deliver songs that are appropriate for a user's emotions, which can change based on their mood, leading to a suboptimal user experience.
Innovation Solution
A music distribution system that includes a server storing song lists categorized by human emotions, where each terminal apparatus captures a user's facial image to estimate their emotion and selects a song from the corresponding list for playback, allowing the server to distribute songs tailored to the user's preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional music distribution systems deliver songs without considering user emotions, then the system is simple and easy to operate, but the user experience is suboptimal because songs are not appropriate for the user's current mood
Solution Approach 1:
The patent introduces an emotion recognition module as an intermediary between the user and the music distribution system. This module captures user images, analyzes emotional states, and translates them into song selection criteria, enabling the system to adapt to user emotions without requiring complex direct user-input interfaces
Solution Approach 2:
The patent replaces manual user input mechanisms (where users would manually select songs or moods) with an automated image-based emotion recognition system. This substitution uses computer vision and AI algorithms to automatically detect and respond to user emotional states, reducing operational complexity while improving adaptability
2Measurement precision
If the system captures and analyzes user images to estimate emotions, then song selection becomes tailored to user preferences, but the device complexity and processing requirements increase
Solution Approach 1:
The patent divides the emotion recognition process into distinct segments: image capture by the terminal apparatus, image transmission to the server, emotion analysis by the emotion recognition module, and song selection based on analyzed emotions. This segmentation allows each component to be optimized independently, managing overall system complexity while maintaining high measurement precision
3Adaptability or versatility
If the server stores multiple song lists categorized by human emotions, then the system can deliver appropriate songs based on user mood, but the data storage and management complexity increases
Solution Approach 1:
The patent organizes the music library with different 'local qualities' by creating distinct song lists categorized according to specific human emotions. Each emotion category contains songs with characteristics suitable for that emotional state, allowing the system to efficiently retrieve appropriate songs without needing to process the entire music library, thus managing data storage effectively while maintaining high adaptability
Data Source
AI summary
A music distribution system 1 comprising a plurality of terminal apparatus 10 each used by a plurality of users and a server 20 configured to communicate with the plurality of terminal apparatus 10, wherein the server 20 stores a plurality of song lists each corresponding to a plurality of classifications of human emotions in a memory 22, each terminal apparatus 10generates a user image by photographing a user of its own apparatus, server 20 acquires, for each terminal apparatus 10, a classification of a user's emotion estimated from the user image to select a song included in the song list corresponding to the classification as a first song, and each terminal apparatus 10 plays the first song selected for its own apparatus.