Neural Network Music Generation Adapting to User and Screen Context
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing music generation devices struggle to create music that dynamically adapts to a user's changing situation, preferences, and environment, as they rely on user input and fail to consider external factors like weather or screen content.
Innovation Solution
An electronic device equipped with neural networks to obtain user situation, screen situation, and external situation information, using a combination of softmax regression, transformer models, and transformer-XL to generate sheet music that aligns with the user's mood and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a music generation device relies on user input to generate music, then the device can produce music based on explicit user preferences, but it fails to reflect various user situations that change over time and cannot automatically adapt to dynamic environments
Solution Approach 1:
The system automatically collects and processes user situation information, screen situation information, and external situation information without requiring explicit user input. The neural network autonomously generates music by self-processing the collected data, enabling the device to serve itself in adapting to user situations dynamically
Solution Approach 2:
The system continuously collects user situation information (from sensors, user profiles), screen situation information (from display content analysis), and external situation information (from environmental sensors), feeds this data into the neural network, and adjusts music generation based on the processed feedback, creating a closed-loop adaptive system
2Measurement precision
If a music generation device uses multiple neural networks to process various situation information, then the music generation accuracy and personalization improve, but the device complexity increases
Solution Approach 1:
The system divides the complex music generation task into multiple specialized neural networks: a first neural network processes user and screen situation information to generate basic music parameters, while a second neural network refines the music generation based on additional contextual factors. This segmentation allows each network to specialize in specific aspects, improving overall accuracy while managing complexity through modular design
Solution Approach 2:
The neural networks are designed to process multiple types of input data (user situation, screen situation, external situation information) and generate comprehensive music parameters simultaneously. This multi-functionality reduces the need for separate specialized systems, managing complexity while maintaining high generation accuracy
Data Source
AI summary
An operation method of an electronic device including obtaining multi-mood information from at least one of user situation information and screen situation information, obtaining metadata from at least one of user preference information, the multi-mood information, and external situation information, and obtaining the sheet music for music performance from the metadata by using at least one neural network.