In this paper, to automatically generate a music for the melody part by deep learning with training data collected from Chopins piano piecies, a combining model of Residual Neural Networks(ResNet) and Long-Short Term Memory Networks (LSTM) are proposed. First, to generate a music for the melody part of a piano music, a training dataset used for deep learning is provided. Secondly, by using each of a LSTM Model and a combining model of LSTM and ResNet,experiments on music generationare presented. Thirdly, the results of music generation by each model are compared and discussed. In conclusion, the principal results are summarized
We demonstrate two generative models created by traininga recurrent neural network (RNN) with three ...
In this paper, we introduce new methods and discuss results of text-based LSTM (Long Short-Term Memo...
We propose an end-to-end approach for modeling polyphonic music with a novel graphical representatio...
This report demonstrated the use of conditioning inputs, together with an appropriate model architec...
Music is closely related to human life and is an important way for people to express their feelings ...
Long Short-Term Memory (LSTM) neural networks have been ef- fectively applied on learning and genera...
In music there are a set of rules a melody must follow in order to sound pleasant to the listener. I...
Music generation is increasingly recognized as an attractive field of study in Deep Learning. This p...
Tato práce se zabývá generováním hudby pomocí rekurentních neuronových sítí. V řešení byly použity m...
Recurrent (neural) networks have been deployed as models for learning musical processes, by computat...
Practicing musical instruments can be experienced as repetitive and boring and is often a major barr...
Music is an essential part of everyone’s life and plays a very important role in many of the media a...
The aim of this thesis is to explore new ways of generating unique polyphonic music using neural net...
Generating convincing music via deep neural networks is a challenging problem that shows promise for...
We apply deep learning methods, specifically long short-term memory (LSTM) networks, to music transc...
We demonstrate two generative models created by traininga recurrent neural network (RNN) with three ...
In this paper, we introduce new methods and discuss results of text-based LSTM (Long Short-Term Memo...
We propose an end-to-end approach for modeling polyphonic music with a novel graphical representatio...
This report demonstrated the use of conditioning inputs, together with an appropriate model architec...
Music is closely related to human life and is an important way for people to express their feelings ...
Long Short-Term Memory (LSTM) neural networks have been ef- fectively applied on learning and genera...
In music there are a set of rules a melody must follow in order to sound pleasant to the listener. I...
Music generation is increasingly recognized as an attractive field of study in Deep Learning. This p...
Tato práce se zabývá generováním hudby pomocí rekurentních neuronových sítí. V řešení byly použity m...
Recurrent (neural) networks have been deployed as models for learning musical processes, by computat...
Practicing musical instruments can be experienced as repetitive and boring and is often a major barr...
Music is an essential part of everyone’s life and plays a very important role in many of the media a...
The aim of this thesis is to explore new ways of generating unique polyphonic music using neural net...
Generating convincing music via deep neural networks is a challenging problem that shows promise for...
We apply deep learning methods, specifically long short-term memory (LSTM) networks, to music transc...
We demonstrate two generative models created by traininga recurrent neural network (RNN) with three ...
In this paper, we introduce new methods and discuss results of text-based LSTM (Long Short-Term Memo...
We propose an end-to-end approach for modeling polyphonic music with a novel graphical representatio...