Finite State Automata for Dynamic Sound Composition
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Solution Overview
Problem
Existing music composition technologies are limited in generating diverse musical styles and require users to have musical knowledge, as they rely on specific chord progressions and ethnic aesthetics, making it difficult for non-musicians to create compositions and limiting the variety of musical outputs.
Innovation Solution
A method using finite state automata to process input sounds, defining nodes and links based on tone, intensity, and duration, and traversing these automata with exploration rules to generate new sound sequences, allowing for over-generation and creation of new musical compositions that can encompass various styles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If computer programs require users to know chord progressions and musical terminology, then the composition quality can be controlled, but the ease of operation deteriorates because non-musicians cannot use such programs
Solution Approach 1:
The patent introduces an intermediary system that automatically analyzes input sounds and generates finite state automata representations, serving as a mediator between the user's simple sound inputs and the complex composition rules. This intermediary processing layer eliminates the need for users to directly understand or specify chord progressions and musical terminology, while still enabling controlled composition quality through the automated analysis and generation process.
2Manufacturing precision
If algorithms are limited to specific ethnic and cultural musical aesthetics, then the manufacturing precision of style-specific compositions is improved, but the adaptability deteriorates because they cannot encompass many musical styles
Solution Approach 1:
The patent creates a universal finite state automata-based composition system that can process and generate music across multiple ethnic and cultural styles. The system analyzes input sounds and automatically determines appropriate stylistic patterns, enabling a single algorithm to function across diverse musical traditions rather than requiring separate algorithms for each style. This universal approach maintains precision within each style while achieving broad adaptability across many musical genres.
Solution Approach 2:
The system dynamically adjusts compositional parameters based on the analyzed input sounds, automatically adapting to different musical styles through parameter transformation. By changing the parameters and rules applied during finite state automata generation based on the characteristics of the input sounds, the system can accurately produce compositions in various ethnic and cultural styles without requiring manual style selection or predefined style-specific algorithms.
3Productivity
If the system processes each input sound independently without history values, then the processing speed is improved, but the manufacturing precision deteriorates because it cannot maintain consistency across sound sequences
Solution Approach 1:
The patent implements preliminary action by pre-processing input sounds to create finite state automata representations and pre-establishing history value structures before actual composition generation. This preliminary organization of sound data into structured automata with predefined history tracking enables the system to maintain sequence consistency without slowing down the actual composition process, as the consistency rules are already embedded in the automata structure.
Solution Approach 2:
The system employs a nested structure where finite state automata are embedded within a history value framework. Each automaton represents a local sound pattern, while the history value context provides the broader sequence framework. This nesting allows the system to process sounds efficiently at the automaton level while simultaneously maintaining overall sequence consistency through the encompassing history structure, achieving both speed and precision.
Data Source
AI summary
Methods for dynamically analyzing input sounds and processing the input sounds to define a new set of output sounds are provided. One method includes receiving a first set of input sounds and a second set of input sounds, where each of the first and second sets of input sounds are processed to identify one of a tone, intensity, or frequency, and a duration. The method defines a node for each identified input sound and a link between the input sounds of the first and second sets of input sounds. The nodes and links from the first and second sets of input sounds create a respective first and second finite state automata. A history value is defined for processing the nodes of the first and second sets of input sounds, and the history value defines a number of previous nodes that will be identical in each of the first and second sets of input sounds before a particular node is shared between the first and second sets of input sounds. Then, the method forms the new set of output sounds from a third finite state automaton that includes nodes from the first and second set of input nodes and nodes that are shared based on meeting the history value.