AI Interactive Character Music Generation via Memory Feature Mapping
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Solution Overview
Problem
Current AI-generated music lacks the ability to respond effectively to the memories and emotional experiences of its listeners, failing to evoke the same emotional closeness and relatability as human-composed music.
Innovation Solution
The development of an AI interactive character (AIIC) system that uses machine learning models and memory data structures to generate creative content, such as music, based on shared memories and emotional contexts, allowing for personalized and relatable compositions that resonate with users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI is used to generate music, then music creation efficiency is improved, but emotional relatability and listener engagement deteriorate
Solution Approach 1:
The system performs preliminary actions by collecting and storing user memory data, emotional responses, and music preferences before music generation. This pre-processing of personal data enables the AI to create emotionally relatable music without compromising generation efficiency, as the framework is established in advance
Solution Approach 2:
The system implements feedback mechanisms where user emotional responses to generated music are captured and used to refine future music creation. This closed-loop feedback allows the AI to continuously improve emotional relatability while maintaining efficient generation through learned patterns
2Adaptability or versatility
If AI generates music based on user data, then personalization is improved, but data privacy and security risks worsen
Solution Approach 1:
The system introduces an intermediary layer that processes user data through anonymization and aggregation techniques. This intermediary framework enables personalization by processing individual preferences while protecting privacy by removing directly identifiable information before analysis
Solution Approach 2:
The system applies different processing qualities to different data elements - sensitive personal information receives enhanced protection and anonymization, while non-sensitive musical preferences are processed with standard personalization algorithms, creating a differentiated privacy protection approach
Data Source
AI summary
A system includes a computing platform having a hardware processor and a memory storing software code, a memory data structure storing memory features for an artificial intelligence interactive character (AIIC), and a trained machine learning (ML) model. The software code is executed to elicit, using the AIIC, a reminiscence from a user, predict, using the trained ML model and the reminiscence, one or more user memory feature(s) of the reminiscence, identify, using the memory data structure, one or more of the memory features for the AIIC as corresponding to the user memory feature(s), and determine, using the user memory feature(s), a mood modifier for a creative composition. The software code is further executed to produce, based on the mood modifier and the corresponding one or more of the plurality of memory features for the AIIC, the creative composition, and provide the creative composition to the AIIC.