Bi-Directional Long Short-Term Memory Neural Networks for Music Composition

Developments in brain organization and deep learning will enable these developments to be used in different fields and different forms of work, producing human-like results. This research uses bidirectional recurrent neural networks (RNNs) and long short-term memory (LSTM) cells to understand the complex relationships that exist between the many notes, pitches, and timbral values that make up music. By doing so, we propose a method for creating music effectively. A method of achieving high performance in music synthesis using a bidirectional repeated neural network using Long Short-Term Memory (LSTM) cells is illustrated by examining different angles associated with the Pokemon midi track. I was. Also consider presenting models using various age groups. The model's output music is consistent thematically and stylistically with the music the model learned to recognise from. The music that is generated can have its pace, instruments, and other elements easily modified.