The invention relates to the technical field of
data analysis and
artificial intelligence, in particular to a historical data-based instrumental poem
analysis method, which comprises the following steps of: acquiring multi-
modal original data containing audio signals, instrumental work symbols and text
evaluation data from a historical instrumental work
database; performing standardized preprocessing to form a
structured analysis data set; based on the
data set, extracting multi-dimensional features such as
timbre variance, force gradient, duration offset,
pitch distribution,
rhythm entropy, chord distance, emotion
score and vocabulary distribution statistics, and constructing a comprehensive poem concept
feature vector; and training the
training set marked with the poem concept style
label by using a deep neural network, constructing a poem concept analysis model, finally realizing poem concept quantitative scoring and style similarity calculation of the instrumental works, and visually outputting a result. According to the method, the defects of strong subjectivity and single dimension of attribute analysis of abstract instrumental works in the prior art are overcome, and objective, multi-dimensional and interpretable automatic analysis of poems and concepts of the instrumental works is realized.