Treffer: Generation of music using LSTM.

This research delves into the interesting field of music generation utilizing machine learning and deep learning approaches. The project focuses on composing music sequences using a special form of neural network called Long Short-Term Memory (LSTM) and the Python Keras module. The project begins by explaining the concept of employing artificial intelligence to make music. It defines important terminology such as Recurrent Neural Networks (RNNs) and LSTM networks, which are great at capturing musical patterns due to their capacity to remember information over lengthy durations. The Music21 Python toolbox is introduced to enable music generation. This toolkit allows you to deal with musical notation from MIDI files and manipulate musical elements like notes and chords. Finally, this project demonstrates the power of AI and LSTM neural networks in the creation of music. The research contributes to the investigation of artificial intelligence's creative potential as well as its role in transforming the world of music creation. [ABSTRACT FROM AUTHOR]

Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)