This invention discloses an
artificial intelligence-based automatic music composition and
lyrics generation
system and method, specifically relating to the field of automatic music composition and
lyrics generation technology. It models the attenuation characteristics of melody
pitch distribution and dynamic changes in a target acoustic environment and extracts the main emotion-carrying
frequency band. It calculates an emotion transmission
attenuation coefficient based on the degree of spectral attenuation, couples the emotion transmission
attenuation coefficient with the temporal distribution relationship of the
lyrics semantics, constructs a temporal evolution sequence of
emotion perception shift, analyzes the alignment relationship between lyric
syllable accents and melody beats, calculates a rhythmic
clarity degradation index, quantifies the degree of rhythmic
ambiguity, and unifies the emotion transmission
attenuation coefficient and rhythmic
clarity degradation index into an acoustic
adaptation degradation
state vector. Based on this vector, it jointly adjusts the melody
pitch distribution,
note value configuration, and lyric
syllable density, adaptively optimizing the emotion expression path and rhythmic structure for different playback terminals and acoustic environments.