Melody Generation via Lyric-Note Correlation Models
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Solution Overview
Problem
Existing algorithmic composition systems do not consider the correlation between melody and lyrics, limiting their ability to generate melodies that effectively match the tone and rhythm of song lyrics.
Innovation Solution
A method that utilizes correlation data to create a composition model based on the patterns between song notes and lyrics, incorporating tone data and syllable identifiers to generate melodies that align with the lyrics, using a probabilistic automaton to execute the tone sequence and produce a melody.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing algorithmic composition systems are used, then automatic melody generation is achieved, but the ability to match tone and rhythm of song lyrics is limited
Solution Approach 1:
The system segments the song structure into distinct components: lyrics are divided into syllables or phonemes, and melodies into musical events with temporal alignment. This segmentation enables precise correlation analysis between lyrical and melodic elements, improving matching accuracy while maintaining manageable system complexity through modular processing stages.
Solution Approach 2:
The patent introduces correlation data as an intermediary element that links lyrics and melodies. This correlation data structure serves as a mediator, capturing the relationships between lyrical segments and melodic segments without requiring direct complex interaction between all system components, thus improving reliability while controlling complexity.
2Measurement precision
If correlation data between notes and words is used, then melody generation accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system performs preliminary processing by pre-computing and storing correlation data between notes and words from existing songs before generating new melodies. This preliminary action creates ready-to-use correlation models that reduce real-time processing requirements, improving measurement precision while minimizing data processing overhead during actual melody generation.
Solution Approach 2:
The patent uses correlation data derived from analyzing existing songs as templates or copies to guide the generation of new melodies. By copying successful correlation patterns from training data, the system achieves high precision alignment without requiring exhaustive real-time analysis of all possible note-lyric combinations, thus reducing processing overhead.
3Manufacturing precision
If multiple correlation analyses are performed, then composition quality is improved, but computational time increases
Solution Approach 1:
The system dynamically adjusts processing parameters based on the complexity of the input lyrics and desired composition quality. By changing parameters such as the granularity of syllable segmentation, the depth of correlation analysis, and the number of correlation models to apply, the system achieves high composition quality while minimizing computational time for simpler cases and allocating more resources only when necessary for complex compositions.
Data Source
AI summary
Disclosed are ways to generate a melody. Currently, no algorithm exists for automatically composing a melody based on music lyrics. However, according to some recent studies, within a song, there usually exists a correlation between a song's notes and a song's lyrics wherein a melody can be generated based on such correlation. Disclosed herein, are systems, methods and algorithms that consider the correlation between a song's lyrics and a song's notes to compose a melody.