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Motifs, phrases, and beyond: The modelling of structure in symbolic music generation
Modelling musical structure is vital yet challenging for artificial intelligence systems that
generate symbolic music compositions. This literature review dissects the evolution of …
generate symbolic music compositions. This literature review dissects the evolution of …
Deep learning's shallow gains: a comparative evaluation of algorithms for automatic music generation
Deep learning methods are recognised as state-of-the-art for many applications of machine
learning. Recently, deep learning methods have emerged as a solution to the task of …
learning. Recently, deep learning methods have emerged as a solution to the task of …
[PDF][PDF] Automatic Stylistic Composition of Bach Chorales with Deep LSTM.
This paper presents “BachBot”: an end-to-end automatic composition system for composing
and completing music in the style of Bach's chorales using a deep long short-term memory …
and completing music in the style of Bach's chorales using a deep long short-term memory …
Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation
Modern psychometric theory provides many useful tools for ability testing, such as item
response theory, computerised adaptive testing, and automatic item generation. However …
response theory, computerised adaptive testing, and automatic item generation. However …
A unit selection methodology for music generation using deep neural networks
Several methods exist for a computer to generate music based on data including Markov
chains, recurrent neural networks, recombinancy, and grammars. We explore the use of unit …
chains, recurrent neural networks, recombinancy, and grammars. We explore the use of unit …
Imposing higher-level structure in polyphonic music generation using convolutional restricted boltzmann machines and constraints
We introduce a method for imposing higher-level structure on generated, polyphonic music.
A Convolutional Restricted Boltzmann Machine (C-RBM) as a generative model is combined …
A Convolutional Restricted Boltzmann Machine (C-RBM) as a generative model is combined …
Investigating the importance of self-theories of intelligence and musicality for students' academic and musical achievement
Musical abilities and active engagement with music have been shown to be positively
associated with many cognitive abilities as well as social skills and academic performance …
associated with many cognitive abilities as well as social skills and academic performance …
Generating structured music for bagana using quality metrics based on Markov models
In this research, a system is built that generates bagana music, a traditional lyre from
Ethiopia, based on a first order Markov model. Due to the size of many datasets it is often …
Ethiopia, based on a first order Markov model. Due to the size of many datasets it is often …
“A Good Algorithm Does Not Steal–It Imitates”: The Originality Report as a Means of Measuring When a Music Generation Algorithm Copies Too Much
Research on automatic music generation lacks consideration of the originality of musical
outputs, creating risks of plagiarism and/or copyright infringement. We present the originality …
outputs, creating risks of plagiarism and/or copyright infringement. We present the originality …
Measuring when a music generation algorithm copies too much: The originality report, cardinality score, and symbolic fingerprinting by geometric hashing
Research on automatic music generation lacks consideration of the originality of musical
outputs, creating risks of plagiarism and/or copyright infringement. We present the originality …
outputs, creating risks of plagiarism and/or copyright infringement. We present the originality …