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Found 5 papers, 1 papers with code
On the Characterization of Expressive Performance in Classical Music: First Results of the Con Espressione Game
In this paper, we offer a first account of this new data resource for expressive performance research, and provide an exploratory analysis, addressing three main questions: (1) how similarly do different listeners describe a performance of a piece?
A Convolutional Approach to Melody Line Identification in Symbolic Scores
The backbone of the method consists of a convolutional neural network (CNN) estimating the probability that each note in the score (more precisely: each pixel in a piano roll encoding of the score) belongs to the melody line.
User Curated Shaping of Expressive Performances
Musicians produce individualized, expressive performances by manipulating parameters such as dynamics, tempo and articulation.
What were you expecting? Using Expectancy Features to Predict Expressive Performances of Classical Piano Music
In this paper we present preliminary work examining the relationship between the formation of expectations and the realization of musical performances, paying particular attention to expressive tempo and dynamics.
From Bach to the Beatles: The simulation of human tonal expectation using ecologically-trained predictive models
Tonal structure is in part conveyed by statistical regularities between musical events, and research has shown that computational models reflect tonal structure in music by capturing these regularities in schematic constructs like pitch histograms.
