DeepAI AI Chat
Log In Sign Up

An approach to Beethoven's 10th Symphony

05/21/2020
by   Paula Muñoz-Lago, et al.
Universidad Complutense de Madrid
0

Ludwig van Beethoven composed his symphonies between 1799 and 1825, when he was writing his Tenth symphony. As we dispose of a great amount of data belonging to his work, the purpose of this paper is to investigate the possibility of extracting patterns on his compositional model from symbolic data and generate what would have been his last symphony, the Tenth. A neural network model has been built based on the Long Short-Therm Memory (LSTM) neural networks. After training the model, the generated music has been analysed by comparing the input data with the results, and establishing differences between the generated outputs based on the training data used to obtain them. The structure of the outputs strongly depends on the symphonies used to train the network.

READ FULL TEXT

page 1

page 2

page 3

page 4

12/14/2017

A Hierarchical Recurrent Neural Network for Symbolic Melody Generation

In recent years, neural networks have been used to generate music pieces...
11/16/2016

Composing Music with Grammar Argumented Neural Networks and Note-Level Encoding

Creating aesthetically pleasing pieces of art, including music, has been...
08/02/2019

LSTM Based Music Generation System

Traditionally, music was treated as an analogue signal and was generated...
05/18/2015

Recurrent Neural Network Training with Dark Knowledge Transfer

Recurrent neural networks (RNNs), particularly long short-term memory (L...
02/25/2021

An introduction to distributed training of deep neural networks for segmentation tasks with large seismic datasets

Deep learning applications are drastically progressing in seismic proces...
12/21/2017

Towards a Deep Improviser: a prototype deep learning post-tonal free music generator

Two modest-sized symbolic corpora of post-tonal and post-metric keyboard...