Musical Composition Application Using Neural Networks for Genre Constraints
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Solution Overview
Problem
Current music composition software is limited in its ability to efficiently create complex musical scores for modern electronic games, as it lacks the capability to recommend musical phrases or adjust notes based on genre-specific constraints and emotional cues, leading to potential reuse of similar musical passages across different projects and failure to conform to specific musical styles.
Innovation Solution
A musical composition application that utilizes machine learning models, such as recurrent neural networks, to recommend musical phrases and adjust notes in real-time, ensuring conformity to specified genres, styles, and emotional themes, while flagging deviations and suggesting updates to maintain musical coherence and originality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a composer manually creates musical scores using traditional music composition software, then the composer can have full control over the composition process, but the time required to create musical scores increases significantly
Solution Approach 1:
The system enables self-service by allowing the music composition application to automatically generate, adjust, and recommend musical phrases based on user input and genre constraints, reducing the manual effort required from the composer while maintaining creative control
Solution Approach 2:
The patent replaces the mechanical manual composition process with an automated system that uses machine learning models (specifically recurrent neural networks) to generate and adjust musical scores, substituting human manual labor with intelligent automation
2Adaptability or versatility
If a composer creates complex music for multiple disparate instruments to match modern device capabilities, then the musical complexity and quality improve, but the time and effort required to compose increases
Solution Approach 1:
The system provides multi-functionality by automatically adapting musical compositions to work with multiple disparate instruments simultaneously, allowing a single composition to be versatile across different instrument configurations without requiring separate compositions for each instrument
3Manufacturing precision
If a composer manually ensures musical phrases conform to genre-specific constraints and rules of counterpoint, then the musical quality and stylistic accuracy improve, but the time required for review and adjustment increases
Solution Approach 1:
The system implements feedback by automatically analyzing generated musical phrases against genre-specific constraints and rules of counterpoint, then providing real-time adjustments and recommendations to ensure conformity, allowing the composer to verify compliance without manual review of each note
Solution Approach 2:
The patent applies preliminary action by pre-configuring genre-specific constraints and rules of counterpoint into the system, so that musical phrases are automatically adjusted to conform to these requirements during generation, rather than requiring post-composition review and adjustment
4Productivity
If a composer creates music for multiple electronic games simultaneously, then the output volume increases, but the risk of unintentionally reusing similar musical passages across different projects increases
Solution Approach 1:
The system acts as an intermediary by automatically tracking and comparing musical phrases across different composition projects, using the machine learning model to identify potential similarities and alert the composer to prevent unintentional reuse, maintaining originality while enabling high productivity
Data Source
AI summary
Systems and methods are provided for enhancements for musical composition applications. An example method includes receiving information identifying initiation of a music composition application, the music composition application being executed via a user device of a user, with the received information indicating a genre associated with a musical score being created via the music composition application. One or more constraints associated with the genre are determined, with the constraints indicating one or more features learned based on analyzing music associated with the genre. Musical elements specified by the user are received via the music composition application. Musical score updates are determined based on the musical elements and genre. The determined musical score updates are provided to the user device.


