AI generated creative content based on shared memories

Number: 12731056
Published: 2026-09-08
Filed: 2023-03-09
Assignee: Disney Enterprises, Inc.
Inventors: Kennedy; James R., Fidaleo; Douglas A., Dohi; Anthony P., Kumar; Komath Naveen, Jiarathanakul; Prutsdom, Hwang; Benjamin, Barron; Michael
CPC: G06N7/01; G10L25/63
Verdict: Low Notable software
First reported: 2026-W37 (2026-09-11)
Source: Google Patents · FreePatentsOnline

The keeper's note

An AI interactive character (AIIC) draws out a user's memories, then generates personalized creative content from them — Disney's memory-aware companion-bot tech.

Abstract

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.

Background

BACKGROUND (1) Creative compositions, such as instrumental and lyrical music for example, are closely associated with human memories. Such memories are often emotional memories (i.e., how a person emotionally reacted while hearing particular music) or intellectual (i.e., where a person was or who they were with while hearing particular music). This close association of music with memories often triggers or evokes pleasant memories of past emotions, people, and places when a piece of music is played. (2) There is evidence in the psychology literature that sharing memories creates a sense of relationship closeness between individuals. The emotional closeness engendered by the sharing of memories is often enhanced when these memories are relatable between the individuals, i.e., the individuals seem to have similar experiences or interpretations of those experiences. In the context of music, this closeness generally is felt when the lyrics, harmony, rhythm or melody performed by an artist trigger an emotional response or evoke memories in a listener. (3) Artificial intelligence (AI) is now being used to create original music. However, until now, AI generated music has had only crude ability to mimic traditionally composed music and may be off-putting rather than enjoyable. Thus, there exists a need in the art for systems and methods for generating music using AI in a manner that is responsive to the memories of its listeners.

Claims

1. A system comprising: a computing platform having a hardware processor and a system memory; the system memory storing a software code, a memory data structure storing a plurality of memory features for an artificial intelligence interactive character (AIIC), and a trained machine learning (ML) model; the hardware processor configured to execute the software code to: elicit, using the AIIC, a reminiscence from a user; predict, using the trained ML model and the reminiscence, at least one user memory feature of the reminiscence; identify, using the memory data structure, one or more memory features of the plurality of memory features for the AIIC as corresponding to the at least one user memory feature, by: applying a weighted similarity calculation across a plurality of dimensions of the at least one user memory feature and the plurality of memory features for the AIIC, to produce a weighted overall similarity score; and selecting the one or more memory features based on the weighted overall similarity score; determine, using the at least one user memory feature, a mood modifier for a creative composition; produce, based on the mood modifier and the one or more memory features, the creative composition; and provide the creative composition to the AIIC. || 12. A method for use by a system including a computing platform having a hardware processor and a system memory, the system memory storing a software code, a memory data structure storing a plurality of memory features for an artificial intelligence interactive character (AIIC), and a trained machine learning (ML) model, the method comprising: eliciting, by the software code executed by the hardware processor and using the AIIC, a reminiscence from a user; predicting, by the software code executed by the hardware processor and using the trained ML model and the reminiscence, at least one user memory feature of the reminiscence; identifying, by the software code executed by the hardware processor and using the memory data structure, one or more memory features of the plurality of memory features for the AIIC as corresponding to the at least one user memory feature, by: applying a weighted similarity calculation across a plurality of dimensions of the at least one user memory feature and the plurality of memory features for the AIIC, to produce a weighted overall similarity score; and selecting the one or more memory features based on the weighted overall similarity score; determining, by the software code executed by the hardware processor and using the at least one user memory feature, a mood modifier for a creative composition; producing, by the software code executed by the hardware processor based on the mood modifier and the one or more memory features, the creative composition; and providing, by the software code executed by the hardware processor, the creative composition to the AIIC.